CN119693198A

CN119693198A - Flight crew safety management methods and systems, equipment, and media

Info

Publication number: CN119693198A
Application number: CN202510199557.0A
Authority: CN
Inventors: 吴杨; 陈志军; 陈军
Original assignee: Zhuhai Xiangyi Aviation Technology Co Ltd
Current assignee: Zhuhai Xiangyi Aviation Technology Co Ltd
Priority date: 2025-02-24
Filing date: 2025-02-24
Publication date: 2025-03-25
Anticipated expiration: 2045-02-24
Also published as: CN119693198B

Abstract

The present application belongs to the field of safety management technology, and specifically relates to a flight crew safety management method and system, equipment, and medium, which aims to solve the technical problem of low safety management accuracy caused by the low accuracy of the existing TEM model. Among them, the method includes: defining multiple risk parameters and state parameters to construct an improved TEM model; using a risk source identification algorithm to identify potential risk sources that appear during the flight of the flight crew, analyzing the potential risk sources, and generating corresponding safety management strategies based on the analysis results; obtaining flight monitoring data generated during the flight crew members' execution of the safety management strategy, and based on the flight monitoring data, quantitatively evaluating the safety management performance of the flight crew members to obtain evaluation results; according to the evaluation results, determining the training goals and content of the flight crew members, so as to conduct personalized training for the flight crew members based on the training goals and content. The solution provided by the present application improves the accuracy of safety management.

Description

Safety management method, system, equipment and medium of flight unit

Technical Field

The embodiment of the application relates to the technical field of safety management, in particular to a safety management method, system, equipment and medium of a flight unit.

Background

Threat and Error Management (TEM) models are widely adopted by the international civil aviation organization, aviation administration of various countries, and various airlines for guiding flight safety Management and crew training. However, in practical applications, there are subtle differences in the definition of key concepts in the TEM model, such as threats, errors, and undesirable aircraft states (Undesired AIRCRAFT STATE, UAS), by different airlines. These differences present challenges to flight crew members in performing training and safety management data processing and other practical activities. For example, some airlines consider that effective management of a threat is completed and then returned to a safe state, but in practice, even if such a threat as engine failure is effectively managed, the flight crew may still be in a single shot operation and obviously cannot be considered to be in a full safe state. Thus, there is an urgent need for a more uniform and flexible method to improve TEM models.

The conventional TEM model is three, and the first conventional TEM model needs to ensure that the meaning of the conventional TEM model can be clearly explained when the conventional TEM model is defined as "safe", and considers the influence of the randomness of the result of the aircraft unit after the error and UAS are managed on the "safe" so as to ensure that the definition can embody the targeting of the effective management of the aircraft unit. The second existing TEM model defines the unsafe outcome as an end state after the linear relationship of threat, error and UAS, which seems to indicate that the final unsafe outcome is of necessity. However, the flight crew is configured in a specific scenario, and if the flight crew is programmed to change after encountering wind shear and the flight crew fails to maintain the regulatory demand altitude, then breaking through the safety altitude is not necessarily an unsafe outcome. While the third existing TEM model is responsible for the occurrence of a threat, even though flight crew members have already implemented competence countermeasures to manage, there is still a possibility of flight crew errors, which in turn results in a reduced safety margin. And when an error or UAS is found and action is taken to resume, it is also most desirable to only enable the flight crew to resume the previous flight. In other words, while many airlines perform security management based on TEM models, many problems are encountered in the implementation. First, the inconsistencies in the data processing methods of companies lead to difficulties in statistical analysis and results application. Second, the definition of "safe" status is not well defined, especially when dealing with undesirable aircraft status caused by threats or errors, and often lacks clear standards. Furthermore, existing models often assume that the final unsafe outcome is a corollary of threat, error, and UAS linear relationships, ignoring the positive impact of the crew after taking effective measures in specific situations. For example, when the aircraft crew successfully addresses wind shear but fails to maintain the height of regulatory requirements, breaking through the safe height does not necessarily mean that unsafe consequences occur.

Therefore, the existing TEM model has defects in terms of flexibility and accuracy, and cannot fully reflect the complexity and variability in practical situations.

Disclosure of Invention

The embodiment of the application provides a safety management method, a safety management system, safety management equipment and safety management media for a flight unit, which are used for solving the problem of low safety management accuracy caused by low accuracy of a TEM model in the prior art.

In a first aspect, an embodiment of the present application provides a method for safety management of a flight crew, including:

defining a plurality of risk parameters including a threat, an error, a first undesirable aircraft state resulting from the threat, and a second undesirable aircraft state resulting from the error, and status parameters including a desired state and an end state, to construct an improved threat and error management TEM model;

Identifying potential risk sources of the aircraft unit in the flight process by adopting a risk source identification algorithm, performing cluster analysis on the potential risk sources to obtain a cluster analysis result, and generating a safety management strategy corresponding to the cluster analysis result according to knowledge, skills and attitudes related to the cluster analysis result so as to enable the aircraft unit to execute the safety management strategy and restore to a desired state;

Acquiring flight monitoring data generated in the process of executing a safety management strategy by flight crew members in a flight crew, and quantitatively evaluating the safety management performance of the flight crew members based on the flight monitoring data to obtain an evaluation result;

And determining training targets and contents of the flight crew members according to the evaluation results, so as to perform personalized training on the flight crew members based on the training targets and the contents, and improve the professional skills and team cooperation capability of the flight crew members.

Optionally, the generating the security management policy corresponding to the cluster analysis result according to the knowledge, skill and attitude related to the cluster analysis result includes:

judging the number of clusters included in the cluster analysis result, wherein one cluster corresponds to one risk parameter, and one risk parameter represents one actual risk source;

if the number of clusters is greater than or equal to two, sorting all the actual risk sources corresponding to the clustering analysis result according to the properties, the influence range and the emergency degree of the actual risk sources;

acquiring knowledge, skill and attitude related to each actual risk source from knowledge, skill and attitude related to the clustering analysis result according to the priority ordering result;

and generating a security management strategy corresponding to each actual risk source according to the knowledge, skill and attitude related to each actual risk source so as to form the security management strategy corresponding to the clustering analysis result.

Optionally, the threat has a priority over the first undesired aircraft state and the second undesired aircraft state has a priority over the error;

The threats include both predictive threats and unpredictable threats, the errors include association errors and spontaneous errors, the predictive threats and the unpredictable threats correspond to different security management policies, and the association errors and the spontaneous errors correspond to different security management policies.

Optionally, the generating, according to knowledge, skills and attitudes related to each actual risk source, a security management policy corresponding to each actual risk source includes:

for the predictable threat, according to the knowledge, skill and attitude related to the predictable threat, the steps in the following processes are sequentially executed, namely, an open communication environment is constructed, a strategy plan is formulated, an initial strategy is determined according to the strategy plan, the task in the initial strategy is divided, the initial strategy is implemented, and the strategy is adjusted;

judging whether a crew member is in a cold state or not for the unpredictable threat, if so, sequentially executing the steps in the following procedures of flight optimization, navigation planning improvement, communication optimization, threat factor identification and management according to knowledge, skills and attitudes related to the unpredictable threat and by combining similar historical coping experience data;

For the associated errors, combining knowledge, skill and attitude of the associated errors, performing self error management by setting a specified short-term target in a specific scene, and performing error management of other flight crew members by a direct aging method;

For spontaneous errors, combining knowledge, skill and attitude of related errors, performing self error management by setting a personal short-term target, and performing error management of other flight crew members by a direct aging method;

For the first unexpected aircraft state, three strategies of stopping, returning and escaping are adopted to recover the aircraft unit to the expected state;

And for the second unexpected aircraft state, three strategies of stopping, returning and escaping are adopted to recover the aircraft unit to the expected state, and then error management is carried out.

Optionally, the steps of performing flight optimization, navigation planning improvement, communication optimization, threat factor identification and management according to the unpredictable threat related knowledge, skill and attitude and in combination with similar historical coping experience data comprise:

Acquiring historical coping experience data similar to the unpredictable threat from a historical database by utilizing a nearest neighbor algorithm according to the occurrence position, occurrence time and influence range of the unpredictable threat;

And dynamically adjusting similar historical coping experience data by using a reinforcement learning algorithm according to the knowledge, skills and attitude related to the unpredictable threat to obtain a safety management strategy corresponding to the unpredictable threat, and performing flight optimization, navigation planning improvement, communication optimization and threat factor identification and management according to the safety management strategy corresponding to the unpredictable threat.

Optionally, the quantitatively evaluating the safety management performance of the flight crew based on the flight monitoring data to obtain an evaluation result, including:

dividing flight monitoring data according to different flight phases to obtain specific data of each flight phase, wherein the flight phases comprise take-off, cruising and landing;

Setting corresponding evaluation indexes for each flight stage, wherein the evaluation indexes comprise at least one of flight parameter deviation, operation response time, task completion degree and team cooperation effect;

according to the specific data of each flight phase, calculating the score of the corresponding evaluation index of the flight crew in each flight phase;

Comparing the score of the evaluation index corresponding to the flight crew member in each flight stage with the preset safety management performance standard corresponding to each flight stage to obtain a comparison result of the evaluation index corresponding to the flight crew member in each flight stage, wherein the comparison result is a performance grade, and different preset safety management performance standards are corresponding to different flight stages;

And generating a performance evaluation report of the flight crew member according to the comparison result, and taking the performance evaluation report as an evaluation result.

Optionally, determining training targets and content of the flight crew member according to the evaluation result includes:

according to the evaluation result, weak links and skills to be lifted, which are existed in the flight process of the flight crew members, are identified, wherein the skills to be lifted are evaluation indexes of which the performance level does not meet the preset level requirements, and the weak links are flight stages corresponding to the evaluation indexes of which the performance level does not meet the preset level requirements;

Aiming at weak links and skills to be improved, selecting corresponding training topics from a preset training topic library, wherein the training topics comprise at least one of wind shear change, communication errors and missed approach management;

According to the training subjects, personalized training targets are determined, according to training contents designed by the training targets, a designated training mode is determined according to habit characteristics of flight crew members, so that training contents are displayed by the designated training mode, the training mode comprises theoretical training and simulator training, the training targets comprise at least one of improving accuracy of flight operation, enhancing emergency response capability, preventing flight task omission and improving team cooperation capability, and the training contents comprise at least one of simulating flight training, emergency scenario exercise, strengthening task list management and team cooperation training.

In a second aspect, an embodiment of the present application provides a safety management system for a flight crew, including:

A definition module for defining a plurality of risk parameters including a threat, an error, a first undesired aircraft state resulting from the threat, and a second undesired aircraft state resulting from the error, and status parameters including a desired state and an end state, to construct an improved threat and error management TEM model;

The identification module is used for identifying potential risk sources of the aircraft unit in the flight process by adopting a risk source identification algorithm, carrying out cluster analysis on the potential risk sources to obtain a cluster analysis result, and generating a safety management strategy corresponding to the cluster analysis result according to knowledge, skills and attitudes related to the cluster analysis result so as to enable the aircraft unit to execute the safety management strategy and restore to a desired state;

the evaluation module is used for acquiring flight monitoring data generated in the process of executing the safety management strategy by the flight crew in the flight crew, and carrying out quantitative evaluation on the safety management performance of the flight crew based on the flight monitoring data to obtain an evaluation result;

And the determining module is used for determining training targets and contents of the flight crew members according to the evaluation results so as to perform personalized training on the flight crew members based on the training targets and the contents and improve the professional skills and team cooperation capability of the flight crew members.

In a third aspect, an embodiment of the present application provides a computing device, including a processing component and a storage component, where the storage component stores one or more computer instructions, and the one or more computer instructions are used to be invoked and executed by the processing component to implement a method for managing safety of a flight crew according to any one of the first aspects.

In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, where the computer program when executed by a computer implements a method for managing safety of a flight crew according to any one of the first aspects.

The embodiment of the application provides a safety management method of a flight unit, which comprises the steps of defining a plurality of risk parameters and state parameters to construct an improved threat and error management TEM model, enabling the plurality of risk parameters to comprise a threat, an error, a first unexpected aircraft state caused by the threat and a second unexpected aircraft state caused by the error, wherein the state parameters comprise an expected state and an ending state, adopting a risk source identification algorithm to identify potential risk sources of the flight unit in the flight process, carrying out cluster analysis on the potential risk sources to obtain a cluster analysis result, generating a safety management strategy corresponding to the cluster analysis result according to knowledge, skills and attitudes related to the cluster analysis result to enable the flight unit to execute the safety management strategy to be restored to the expected state, acquiring flight monitoring data generated in the process of executing the safety management strategy by the flight unit member in the flight unit, carrying out quantitative evaluation on the safety management effect of the flight unit member based on the flight monitoring data to obtain an evaluation result, determining training targets and contents of the flight unit member according to the evaluation result, and carrying out personalized training on the flight unit member based on the training targets and contents, and improving the performance of the flight unit member.

The embodiment of the application provides a safety management method of a flight unit, which constructs a more comprehensive and dynamic TEM model by defining a plurality of risk parameters and state parameters. The model encompasses not only conventional threats and errors, but also first and second undesired aircraft states, as well as desired and end states, induced by them. The method solves the problem of fuzzy definition existing in the conventional TEM model and provides a clearer safety standard. In addition, a risk source identification algorithm is adopted and clustering analysis is carried out, so that potential risk sources can be identified in real time, and a personalized security management strategy can be generated according to specific situations. Through the quantitative evaluation of the flight monitoring data, the training targets and the content of the flight crew members can be accurately determined, so that the professional skills and team cooperation capability of the flight crew members are improved. Therefore, the safety management method of the flight unit overcomes the defects of the prior art in terms of flexibility and accuracy by enhancing the adaptability and accuracy of the TEM model, provides a more scientific and effective tool for flight safety management, and further improves the accuracy and the effectiveness of the safety management of the flight unit. Furthermore, the application overcomes the problems of insufficient flexibility and insufficient accuracy in the prior art by introducing a data analysis technology and a dynamic adjustment mechanism, provides a more scientific, efficient and flexible flight safety management mode, not only improves the overall level of flight safety, but also provides technical support for training and development of flight crew members.

These and other aspects of the application will be more readily apparent from the following description of the embodiments.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for safety management of a flight crew according to an embodiment of the present application;

FIG. 2 is a schematic illustration of an improved threat and error management TEM model provided by an embodiment of the application;

FIG. 3 is a schematic structural diagram of a safety management system for a flight unit according to an embodiment of the present application;

Fig. 4 is a schematic structural diagram of a computing device according to an embodiment of the present application.

Detailed Description

In order to enable those skilled in the art to better understand the present application, the following description will make clear and complete descriptions of the technical solutions according to the embodiments of the present application with reference to the accompanying drawings.

In some of the flows described in the specification and claims of the present application and in the foregoing figures, a plurality of operations occurring in a particular order are included, but it should be understood that the operations may be performed out of order or performed in parallel, with the order of operations such as 11, 12, etc., being merely used to distinguish between the various operations, the order of the operations themselves not representing any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to fall within the scope of the application.

Fig. 1 is a flowchart of a method for safety management of a flight unit according to an embodiment of the present application, as shown in fig. 1, where the method includes:

S11, defining a plurality of risk parameters and state parameters to construct an improved threat and error management TEM model, wherein the plurality of risk parameters comprise a threat, an error, a first undesirable aircraft state caused by the threat, and a second undesirable aircraft state caused by the error, and the state parameters comprise a desired state and an end state.

Threat is understood to mean the occurrence of events or errors outside the scope of flight crew influence, which increases the complexity of the flight crew operation. The embodiment of the application manages the threat and can maintain the safety margin. Alternatively, threats may be classified into predictable threats and unpredictable threats.

It should also be understood that an error refers to the intent of an off-organization or flight crew or the intended flight crew as or without. Also, an unmanaged or mismanaged error may result in a second undesirable aircraft state. Errors can be classified into association errors and spontaneous errors, wherein association errors are situations represented by unmanaged or invalid management of a flight crew when a threat occurs, and spontaneous errors are errors caused by the flight crew when no threat occurs.

Undesired aircraft conditions refer to aircraft conditions characterized by deviations from common parameters during operation (e.g., aircraft position or speed deviations, improper use of flight controls, or incorrect system configuration), and aircraft refers to components in a flight crew. It should be noted that the undesired aircraft state is related to a decrease in safety margin. Wherein the UAS (T) and the second undesired aircraft state UAS (E) represent two different types of undesired aircraft states, respectively. UAS (T) refers to an undesired aircraft condition directly caused by a threat, and UAS (E) refers to an undesired aircraft condition caused by a flight crew error.

Illustratively, the improved threat and error management TEM model is shown in FIG. 2, including threat, spontaneous error, associated error, UAS (T), UAS (E), and also including auto-recovery, active management, unmanaged or inactive management, expected state, and end state.

The automatic recovery means that when the threat and the error occur and the aircraft set is not managed or not managed, the aircraft set can sometimes automatically recover to a desired state, and the reason may be that the adjustment of the flight operation or the operation program of the airline company has higher safety redundancy. Effective management refers to the formation of a coping scheme by the presentation of competence by the flight crew, and the management of threats, errors and undesired aircraft states according to the safety management policies in the coping scheme. The expected state refers to a dynamic objective state after the aircraft crew is expected to manage. The expected state is irrelevant to the security rating adopted by the current security management, and the embodiment of the application can grade the security management from the security management perspective, and different grading data can trace the security management flow of threat, error and unexpected aircraft state or optimize the security management policy of threat, error and unexpected aircraft state. An end state may refer to an irreversible objective state resulting from unmanaged or unmanaged UAS of an undesired aircraft state.

Thus, the improved TEM model is a threat and error management system for "full-dimension TEM 360". The threat and error management system integrates a data analysis framework and is used for comprehensively optimizing threat and error management processes in aviation operation and training, and improving flight safety margin and training effectiveness. The improved TEM model constructs an omnibearing and multi-layer management framework by defining terms such as threat, error, unexpected Aircraft State (UAS), expected state and ending state and the like, and realizes closed-loop management of the whole process from threat, error and UAS identification to effective response.

By constructing an improved TEM model, the embodiment of the application can clearly obtain full views of the system logic and the event flow participated by the flight crew, including the initiation and termination of unsafe events. According to the embodiment, the safety management of the aircraft unit is carried out on the whole flow, so that the safety of the aircraft unit can be integrally improved, and finally, the comprehensive safety target is realized. By constructing an improved TEM model, the embodiment of the application can more systematically identify and solve potential safety hazards, thereby constructing a more robust and reliable safety management system.

To enable efficient application of the improved TEM model, embodiments of the present application may design a corresponding TEM list that is available for download from the pilot full lifecycle management module. The elements of the TEM list include case codes, event numbers, event codes, event management conditions, flight phases, event descriptions, threat numbers, threat management, threat impact, error numbers, error types, error feedback, error management conditions, undesired aircraft states, management conditions for undesired aircraft states, final states, programs, communications, automated path management, manual path management, knowledge applications, pilot and team collaboration, decisions, situational awareness, workload management conditions, training ideas, training topics, and the like.

In order to simplify the application of the improved TEM model, the embodiment of the application can divide the TEM tool into three modules based on the constituent elements of the TEM list.

Specifically, the first module, the risk source identification module is configured to execute the following step S12, take the threat, the error and the unexpected state of the aircraft identified by the front end of the aircraft unit as actual risk sources, and classify the actual risk sources as training scene elements. This classification helps embodiments of the present application systematically identify and analyze various risk factors that may be encountered by the front end of a flight crew.

The second module, based on competence module, is to set different security management strategies for threat, error and management level of unexpected aircraft state, and classify the different security management strategies as competence-based elements. Competence-based modules may enable flight crew members to effectively address and mitigate risk through specific capabilities and skills to determine performance of human factors and explicit training goals.

And a third module, a result performance based module, for managing the final result after implementation (i.e., safety performance), the final result being categorized as a result performance guide element. The outcome performance based module may evaluate the effectiveness of the safety management measures and the overall performance of the flight crew by quantifying the metrics.

To guide course development using big data analysis, embodiments of the present application will take a methodology based on outcome performance. First, the severity of unsafe events is ranked, and overall training goals are set accordingly, to reduce the probability of corresponding types of events. And then, carrying out quantitative assignment on each level of event, and further carrying out fine classification and cluster analysis on risk sources of corresponding threats, errors and unexpected aircraft states. The process can define the training subjects and the sub-subjects thereof through Mapping technology (Mapping), so as to ensure that the training content fits the actual risk. Finally, by combining the results of risk analysis, the embodiment of the application can further determine the commonality deficiency of the flight unit group in competence, namely, the group competence short plates. The embodiment of the application can give out specific behaviors of the aircraft unit under specific conditions, and accurately position the training target, thereby designing a training course which meets the actual requirements and is efficient and feasible.

S12, identifying potential risk sources of the aircraft unit in the flight process by adopting a risk source identification algorithm, performing cluster analysis on the potential risk sources to obtain a cluster analysis result, and generating a safety management strategy corresponding to the cluster analysis result according to knowledge, skills and attitudes related to the cluster analysis result so as to enable the aircraft unit to execute the safety management strategy and restore to a desired state.

Where a potential risk source refers to a factor or condition that may pose a threat to flight safety. These factors or conditions do not lead to practical safety problems, but there is a possibility of causing accidents or unsafe events. The risk source identification algorithm is a technique for automatically identifying and classifying potential risk factors by analyzing a large amount of historical data and real-time data to identify factors that may pose a threat to flight safety and help flight crew to take preventive measures or countermeasures in advance. Illustratively, an airline company uses a risk source recognition algorithm based on machine learning to recognize high risk areas (such as common thunderstorm areas) on a specific airline or high fault types (such as engine overheating caused by high temperature in summer) in a specific period of time from data sources such as weather forecast data, flight plan data, historical accident reports and the like, and when a flight is detected to enter a known high risk area, the airline company automatically reminds a crew member and provides corresponding avoidance suggestions or emergency treatment schemes. Cluster analysis is used to divide a set of potential risk sources into several categories (clusters) such that the potential risk sources in the same category have a higher similarity, while the potential risk sources between different categories have a greater variance. Alternatively, the cluster analysis algorithm used for the cluster analysis may be a K-means clustering algorithm.

In the safety management of the flight crew, knowledge, skills and attitudes related to the clustering analysis result are used for making personalized training contents and coping strategies, and the comprehensive capacity of the flight crew members is improved. By way of example, a high risk situation, namely 'air traffic conflict', is discovered through cluster analysis, and the corresponding knowledge is that air traffic rules, airspace division and avoidance principles are known. The skill is to master radar operation, radio communication skills and emergency avoidance procedures. The attitudes are that the coldness, the breaking decision and the team cooperation are kept. For this type of risk, airlines can design specialized training courses, including theoretical explanation, simulated training and case analysis, to ensure that each flight crew member can properly deal with in actual operation.

S13, acquiring flight monitoring data generated in the process of executing a safety management strategy by the flight crew in the flight crew, and quantitatively evaluating the safety management performance of the flight crew based on the flight monitoring data to obtain an evaluation result.

The flight monitoring data refer to various parameters and information collected in the flight process, including aircraft states, environmental conditions, unit operation records and the like, and are used for evaluating the safety condition in the flight process, identifying the execution effect of the safety management strategy and providing basis for subsequent strategy optimization.

By way of example, the embodiments of the present application may analyze altitude, speed, heading, fuel, weather conditions, crew dialog, etc., identify flight conditions within certain specified periods, and formulate targeted improvements based on the flight conditions, such as adjusting flight plans, optimizing operational flows, or enhancing related training.

S14, determining training targets and contents of the flight crew members according to the evaluation results, so as to perform personalized training on the flight crew members based on the training targets and the contents, and improving the professional skills and team cooperation capability of the flight crew members.

Where training goals refer to specific effects that are desired to be achieved through training, and training content is specific courses and activities designed to achieve these goals. Training goals and content are used to promote crew expertise and team collaborative ability, ensuring that they can react correctly in a variety of situations.

By executing S11-S14, the embodiment of the application provides a safety management method of a flight unit, and a more comprehensive and dynamic TEM model is constructed by defining a plurality of risk parameters and state parameters. The model encompasses not only conventional threats and errors, but also first and second undesired aircraft states, as well as desired and end states, induced by them. The method solves the problem of fuzzy definition existing in the conventional TEM model and provides a clearer safety standard. In addition, a risk source identification algorithm is adopted and clustering analysis is carried out, so that potential risk sources can be identified in real time, and a personalized security management strategy can be generated according to specific situations. Through the quantitative evaluation of the flight monitoring data, the training targets and the content of the flight crew members can be accurately determined, so that the professional skills and team cooperation capability of the flight crew members are improved. Therefore, the safety management method of the flight unit overcomes the defects of the prior art in terms of flexibility and accuracy by enhancing the adaptability and accuracy of the TEM model, provides a more scientific and effective tool for flight safety management, and further improves the accuracy and the effectiveness of the safety management of the flight unit.

In one possible embodiment, in S12, generating a security management policy corresponding to the cluster analysis result according to knowledge, skills and attitudes related to the cluster analysis result includes:

Step 121, judging the number of clusters included in the cluster analysis result, wherein one cluster corresponds to one risk parameter, one risk parameter represents one actual risk source, if the number of clusters is greater than or equal to two, executing step 122, otherwise, skipping step 122, and directly executing step 123.

And step 122, according to the properties, the influence range and the emergency degree of the actual risk sources, sequencing all the actual risk sources corresponding to the clustering analysis result in priority.

It should be appreciated that the threat has a priority over the first undesirable aircraft state and the second undesirable aircraft state has a priority over the error, the threat including both a predictable threat and an unpredictable threat, the error including an associated error and a spontaneous error, the predictable threat and the unpredictable threat corresponding to different security management policies and the associated error and the spontaneous error corresponding to different security management policies.

And step 123, acquiring the knowledge, skill and attitude related to each actual risk source from the knowledge, skill and attitude related to the clustering analysis result according to the priority ranking result.

And 124, generating a security management policy corresponding to each actual risk source according to the knowledge, skill and attitude related to each actual risk source so as to form the security management policy corresponding to the clustering analysis result.

As a possible implementation manner, step 124, generating, according to knowledge, skills and attitudes related to each actual risk source, a security management policy corresponding to each actual risk source includes:

For the predictable threat, according to the knowledge, skill and attitude related to the predictable threat, the steps in the following processes are sequentially executed, namely, an open communication environment is constructed, a strategy plan is formulated, an initial strategy is determined according to the strategy plan, the task in the initial strategy is divided, the initial strategy is implemented, and the strategy is adjusted.

And judging whether the crew member is in a cold state or not for the unpredictable threat, if so, sequentially executing the steps in the following flow, namely carrying out flight optimization, navigation planning improvement, communication optimization, threat factor identification and management according to knowledge, skills and attitudes related to the unpredictable threat and combined with similar historical coping experience data.

The method comprises the steps of a1, obtaining historical coping experience data similar to the unpredictable threat from a historical database by utilizing a nearest neighbor algorithm according to the occurrence position, the occurrence time and the influence range of the unpredictable threat, a2, dynamically adjusting the similar historical coping experience data by utilizing a reinforcement learning algorithm according to the knowledge, the skill and the attitude related to the unpredictable threat to obtain a safety management strategy corresponding to the unpredictable threat, and carrying out flight optimization, navigation planning improvement, communication optimization and threat factor identification and management according to the safety management strategy corresponding to the unpredictable threat.

By executing the steps a 1-a 2, the embodiment of the application acquires the historical coping experience data similar to the current unpredictable threat from the historical database by utilizing the nearest neighbor algorithm, ensures that the preliminary coping strategy based on the actual case has higher reliability and applicability, combines the latest knowledge, skill and attitude related to the unpredictable threat, dynamically adjusts the historical coping experience data by utilizing the reinforcement learning algorithm, and generates a highly customized safety management strategy. This dynamic adjustment not only takes into account the latest aviation security specifications and technological advances, but also is optimized for specific strategies. Therefore, through the two-step operation, the embodiment of the application can realize more accurate flight optimization, navigation planning improvement, communication optimization and threat factor identification and management, thereby improving the response speed and coping effect of the flight unit in the face of unpredictable threat, and finally effectively reducing the flight risk and guaranteeing the flight safety. The method improves the accuracy and timeliness of emergency response and reduces potential safety hazards.

For the association errors, the knowledge, skill and attitude of the association errors are combined, the self error management is carried out by setting a specified short-term target in a specific scene, and the error management of other flight crew members is carried out by a direct aging method. For spontaneous errors, the knowledge, skill and attitude of the associated errors are combined, self error management is performed by setting personal short-term targets, and error management of other flight crew members is performed by a direct aging method.

The direct aging method may specifically be a Challenge-Alert-Challenge (PACE). The general idea of error management is, therefore, on the one hand, to achieve self-my error management by setting short-term objectives, and on the other hand, to identify and manage other aircraft groups by enhancing their flow proficiency and by PACE direct aging.

For a first undesirable aircraft condition, three strategies of stopping, returning, and escaping are employed to restore the aircraft crew to the desired condition. And for the second unexpected aircraft state, three strategies of stopping, returning and escaping are adopted to recover the aircraft unit to the expected state, and then error management is carried out.

In other words, the management policy for the first undesired aircraft state UAS (T) refers to returning the aircraft crew to the desired state by stopping, returning, escaping three policies before the threat is identified, and subsequently switching to the security management policy corresponding to the threat once the threat is identified. And the management strategy for the second unexpected aircraft state UAS (E) refers to that when the error and the second unexpected aircraft state occur simultaneously, the aircraft unit is returned to the expected state through three strategies of stopping, returning and escaping, and then the safety management strategy corresponding to the error is adopted for managing the error.

The embodiment of the application has the advantages that (1) the crew members can quickly identify and respond various threats and errors by setting different safety management strategies aiming at different actual risk sources, the decision time is reduced, the emergency response speed is improved, and the influence of potential risks on flight is reduced. (2) The effectiveness and pertinence of the countermeasure are improved, and the inefficiency or error possibly caused by the countermeasure mode of 'one-cut' is avoided. (3) Mutual support and cooperation among team members are promoted, coping capacity and management level are improved continuously, and more graceful coping can be ensured when similar conditions are met in the future. (4) the flying safety and the operation efficiency can be improved. Therefore, the embodiment of the application not only improves the safety in the flight process through the specific countermeasure, but also forms a continuous improvement and learning mechanism to ensure that the optimal safety state can be achieved in each flight.

By executing steps 121-124, the embodiment of the application provides a systematic risk management framework, which ensures the comprehensiveness and high efficiency of flight safety. Specifically, the number of actual risk sources is determined by judging the number of clusters in the cluster analysis result, so that each risk parameter is ensured to be independently identified and processed. And (3) carrying out priority ranking according to the nature, the influence range and the emergency degree of the risk sources, so that the most urgent and most threatening risks can be preferentially processed, and the resource allocation is optimized. Specific coping elements related to each risk source are extracted from three dimensions of knowledge, skills and attitudes, and a basis is provided for the subsequent detailed coping measures. A targeted security management policy is generated according to the elements, so that each risk is ensured to have a specific coping scheme. The method not only improves the accuracy and efficiency of risk handling, but also improves the overall flight safety through dynamic adjustment and individuation strategies, and forms a closed-loop safety management system, so that the flight unit can maintain the optimal state in complex and changeable flight environments.

In one possible embodiment, in S13, performing a quantitative evaluation on the performance of safety management of the flight crew based on the flight monitoring data to obtain an evaluation result, including:

And 131, dividing the flight monitoring data according to different flight phases to obtain specific data of each flight phase, wherein the flight phases comprise take-off, cruising and landing. It will be appreciated that each flight phase has specific risks and challenges, and that the refined data helps to specifically identify and manage the risks of these specific phases. The performance of each stage can be independently evaluated, and the problem that some key stages are ignored due to the overall evaluation is avoided.

Step 132, setting corresponding evaluation indexes for each flight phase, wherein the evaluation indexes comprise at least one of flight parameter deviation, operation response time, task completion degree and team cooperation effect. Step 132 encompasses multiple dimensional assessment metrics, ensuring a comprehensive assessment of various aspects of the flight operation. The use of uniform evaluation criteria allows the performance of different crew members to be compared on the same basis.

Step 133, calculating the score of the evaluation index corresponding to each flight phase of the flight crew member according to the specific data of each flight phase. Step 133 converts the qualitative information into quantitative data for subsequent statistical analysis and decision making. The influence of subjective factors is reduced, and more objective and fair assessment results are provided.

Step 134, comparing the score of the evaluation index corresponding to each flight stage of the flight crew member with the preset safety management performance standard corresponding to each flight stage to obtain a comparison result of the evaluation index corresponding to each flight stage of the flight crew member, wherein the comparison result is a performance grade, and different flight stages correspond to different preset safety management performance standards. Step 134 determines whether the performance of each stage meets the expected requirement by comparing with the preset standard. Links with poor performance are quickly identified, so that corrective measures can be conveniently taken in time.

And 135, generating a performance evaluation report of the flight crew member according to the comparison result, and taking the performance evaluation report as an evaluation result. Step 135 presents the evaluation results intuitively in the form of reports, which is convenient for the management layer and crew members to understand, and provides basis for subsequent training and development, and helps the flight crew members to continuously improve their own abilities.

By executing the steps 131-135, the embodiment of the application covers all potential risk points comprehensively, improves the overall flight safety, reasonably distributes resources according to the evaluation result, preferentially solves the links with poor performance, maximizes the utilization of limited resources and improves the overall operation efficiency. And, the performance evaluation report is generated regularly, the experience teaching and training is summarized, the coping strategy is gradually optimized, and the safety management level is continuously improved. Moreover, team collaboration effects are evaluated, facilitating communication and collaboration among crew members. And the expertise and emergency response capability of each member are pertinently improved, and the overall team capability is further improved.

Based on the steps 131-135, S14, determining training targets and contents of the flight crew member according to the evaluation result, including:

And 141, identifying weak links and skills to be improved, which exist in the flight process of the flight crew members, according to the evaluation result, wherein the skills to be improved are evaluation indexes of which the performance grade does not meet the preset grade requirement, and the weak links are flight stages corresponding to the evaluation indexes of which the performance grade does not meet the preset grade requirement.

Step 142, selecting a corresponding training theme from a preset training theme library aiming at weak links and skills to be promoted, wherein the training theme comprises at least one of wind shear change, communication error and missed approach management.

Optionally, the embodiment of the application can set training subjects corresponding to the predictable threat management, the unpredictable threat management, the error management and the unexpected aircraft state management respectively. Or the flight crew member is guided to manage the multi-threat and the error under the complex condition through a simple and feasible safety management strategy by providing a plurality of training topics by a training supervisor unit in the embodiment corresponding to the multi-threat and the error under the complex condition in consideration of the complex and changeable environment of the flight crew during the actual operation process.

Step 143, determining a personalized training target according to a training theme, determining a designated training mode according to the training content designed by the training target and the habit characteristics of the flight crew member so as to display the training content by using the designated training mode, wherein the training mode comprises theoretical training and simulator training, the training target comprises at least one of improving the accuracy of flight operation, enhancing emergency response capability, preventing flight task omission and improving team cooperation capability, and the training content comprises at least one of simulated flight training, emergency scenario training, enhanced task list management and team cooperation training.

By executing steps 141-143, the embodiment of the application provides a systematic and personalized training mechanism, which ensures continuous improvement and optimization of the capability of flight crew members. Specifically, through detailed performance evaluation results, weak links and skills needing to be improved in the flight process are accurately identified, and the evaluation indexes which do not reach the preset level requirements and the corresponding flight stages are clearly pointed out. And selecting proper training topics (such as wind shear change, communication errors and missed approach management) from a preset training topic library, and performing special training on the weak links. Personalized training targets and contents are formulated according to the selected training subjects, and an optimal training mode (such as theoretical training or simulation machine training) is selected by combining habit characteristics of flight crew members, so that each member can learn and promote in an environment which is optimal for the user. The method not only improves the pertinence and the effectiveness of training, but also improves the professional skills and the emergency response capability of the whole team through a personalized training mode, and forms a continuously improved learning and growing system.

By combining the specific scheme provided by the flow, the embodiment of the application can be used for describing the safety management method of the flight unit from the application angle of the TEM tool as follows:

TEM tool has extensive application value in a plurality of scenes such as data analysis, course development, training implementation and flight crew training. Through make full use of TEM instrument, the airline can develop training and safety management work more scientifically, high-efficient, promotes the knowledge and the skill level of flight crew member, helps promoting the safety management level and the operating efficiency of whole aviation industry, and then can promote the sustainable development of aviation industry.

(1) For a data analysis scenario, the following description is given to the embodiment of the present application:

Through the application of TEM tools, flight crew members can more comprehensively identify and manage threats and errors in the flight process, reduce the occurrence of unsafe events and improve the flight safety. The risk source identification module is a key component of the TEM tool and is used for classifying threats, errors and unexpected aircraft states identified by the front end of the aircraft unit into actual risk sources or training scene elements, and further safety management performance evaluation can be carried out on the actual risk sources. In addition, the embodiment can prioritize a plurality of real risk sources which are simultaneously appeared according to the nature, the influence range and the emergency degree of the risk sources.

By systematically identifying and analyzing the risk sources, the embodiment of the application can provide the decision maker with the risk sources, the influence range of the risk sources and the safety management strategy aiming at the risk sources, thereby being beneficial to making effective decisions and ensuring resource conservation. The method has the advantages that potential safety hazards can be found and eliminated in time, and flying crew members are prevented from being exposed to excessive risk sources, so that the operation safety of the flying crew is improved. Secondly, the flight crew members can be trained in a targeted manner so as to improve the safety management efficiency.

(2) Aiming at course development scenes, the following description is made in the embodiment of the application:

In the field of safety management of aircraft units, facing the management level of threats, errors and non-expected aircraft states, a competence-based module provides a corresponding safety management strategy for solving risk problems. Competence-based modules enable flight crew members to effectively address and mitigate risks through specific capabilities and skills, thereby ensuring flight safety.

The training subjects are integrated, and firstly, the threats and the errors can be clustered through the risk source identification module. Secondly, the actual knowledge, skills and attitudes required for constructing the corresponding security management strategy are identified through a competence-based module, and then the knowledge, skills and attitudes are clustered to obtain the training theme.

The list employed by the training topics includes the threat, code of the error or UAS, the specific type of threat, error or UAS, training topics, subtopics, knowledge, skills, attitudes, and may also include accents, notes, topic descriptions, etc. Exemplary, code B, represents an environmental threat.

The code corresponding to the meteorological condition is B01, the mapped training theme is severe weather, the mapped sub-theme is thunderstorm, and the knowledge is the knowledge (such as forming principle, development process and dissipation mechanism) of the weather related to the storm, and the rule of the thunderstorm around the fly operation, the knowledge of the model meteorological radar, the countermeasure of the emergency such as electrostatic discharge, lightning stroke and the like. The skills comprise analyzing the meteorological data of the navigation path and the destination, evaluating the influence of thunderstorm weather on the flight, identifying the meteorological features of the thunderstorm weather, using meteorological monitoring tools such as satellite cloud pictures and the like, judging the exact position, nature, range, strength, direction and the like of the thunderstorm, planning a path around the flight, planning strategies or tactics (including the calculation of the path around the navigation path, oil quantity, airport preparation and the like), and communicating capability. Attitudes include pre-analysis and active analysis. Important contents include round-the-fly path planning, strategy/tactics, and communication modes among flight crew members.

Hail corresponds to code B01.02 and is not trainable, so there is no corresponding subtopic, knowledge, skill, attitude, etc.

The code corresponding to the icing condition is B01.03, the mapped training theme is bad weather, the subtopic is the icing condition, and the knowledge is the definition of the icing condition, the icing type, the icing azimuth and the influence range (such as starting type and maneuvering performance), the icing area information of the weather message, the treatment program, the working principle of the machine type deicing and anti-icing system and the use method. Skills include assessing icing risk, specifying a corresponding flight plan and emergency plan, using deicing or anti-icing systems and related checklists, handling strategies in the event of equipment failure or severe icing, adjusting flight parameters (e.g., adjusting attitude and speed to mitigate the effects of icing on flight) based on disease conditions. Attitudes include alertness to icing conditions. Important contents include round-the-fly path planning, strategy/tactics, and communication modes among flight crew members.

The list of training topics may correspond to knowledge, skills, and attitudes of the individual training sub-topics, which may be downloaded in the pilot full lifecycle management module.

As course developers, the corresponding security management policies under each topic can be defined-competence, and the standard definition of competence is one dimension used to effectively predict and evaluate the flight crew work performance level. The embodiment of the application can use the related knowledge, skills and attitudes under specific conditions so as to show and observe the behavior of the flight crew member to execute the activities or tasks. When a course developer calls a scene element with a competence target or a training theme, the knowledge, skills and attitude requirements are paid attention to, so that the scene has better reality and the training efficiency is improved.

Through the analysis, the training stage work is facilitated, firstly, the knowledge, skill and attitude requirements of different layers can be achieved through different training equipment, and secondly, when a simulator instructor calls a scene, targeted teaching can be carried out, and setting of scene elements can be completed more purposefully.

(3) For training implementation scenarios, the following description is given to the embodiments of the present application:

the training of the TEM tool can improve the professional skills and team cooperation capability of the flight crew members, so that the flight crew members can better cope with complex flight environments, and the flight performance is improved.

During theoretical training, the embodiment can call related threats and errors according to different theoretical training subjects, and then guide the flight unit to analyze a competence-based module, so that the flight unit can learn in a real flight case, and can be beneficial to subsequent simulation machine training or actual running environments. It should be noted that the method can also be extended to training of cabin units or to combined training of units.

In the training of the simulator, the risk source identification module and the competence-based module can play a role in the training stages of pre-voyage assessment, scene assessment or training units, post-voyage assessment and the like.

Specifically, during pre-voyage comment, an instructor can threaten for example, and the instructor can predictably threaten that an open communication environment is adopted, a scheme is planned, a scheme is determined, a task is definitely divided into a work, a specific implementation is carried out, and a strategy is adjusted, and the instructor can unpredictably threaten that the instructor is calm, flying, navigating, communicating, identifying and managing. Through the execution of the safety management strategy, the flight crew can be helped to establish a basic thought for coping with the training mode, and the thought can also be used in actual flight.

In the training unit, the risk source identification module may help the instructor or the inspector build a more efficient framework through previous analytical preparations. The development of the digital platform should also be beneficial to teaching work, and the development is performed around scene elements called by the current risk source identification module so as to reduce the workload of instructors and examers in training implementation.

In the post-voyage comment stage, a TEM tool can cover performance improvement nodes concerned by students in a guidance direction with the students as a center, and can effectively help the instructor and the inspector to establish clear comment ideas.

(4) For a flight crew training scenario, the following description is made in the embodiments of the present application:

The purpose of training is to improve performance of flight crew members, whose growth and development is complex and multidimensional. Thus, knowledge, skills, and attitudes are circulated between flight crew members and interact. The TEM tool is used as an effective training tool, can help instructors and examrs to better guide first-line flight crew members to train and run, and ensures consistency and objectivity of training by unifying speech and operation and standard.

Instructors and examrs act as key roles in the training process, and the quality and the capability of both parties directly influence the quality and the effect of training. Therefore, training work of instructors and examers is also important. Training of instructors and examers is performed through TEM tools, so that the instructors and examers can be ensured to have the use capability of the tools, and the instructors can be better guided to perform training and operation. In teaching practice, the application of TEM tools enables instructor consistency work to be conducted in order and to produce positive utility.

Training and safety management flight crew training using unified TEM tools helps to reduce misunderstanding and ambiguity, improve accuracy and efficiency of information transfer, and also may produce positive efficacy. The TEM tool becomes a common and standard in the industry, which helps to promote standardization and standardization of the whole industry on safety management, and saves resources required to be invoked for training and safety management.

The embodiment of the application describes the training subjects mapped among threat, error and UAS, wherein more training items are firstly trained repeatedly for events with serious consequences (namely typical accidents). This training method, while capable of improving the ability of flight crew members to handle certain specific situations, does not cover all possible safety risks. In addition, as new events continue to appear, these new events are simply added to the training scene library, resulting in training items becoming increasingly bulky and complex, eventually possibly forming a "checkbox" type training method, i.e., as soon as all specified training items are completed, they are considered to meet the safety standards. This is a typical past flight crew training regimen based on experience or hours.

The training objective set in this embodiment is related training performed by taking various competence of the flight crew member as the objective, and there are two important concepts for the competence-based module, that is, one competence needs to be displayed under a specific condition, and the other competence can be transferred under a certain condition.

How the training carrier is selected for competence-based training becomes critical. Therefore, how to make training efficient, effective and effective under the condition of fixed input resources is a problem to be solved. Therefore, the training program set in the embodiment is based on scientific evidence, the training program is formulated and the training effect is evaluated, and the learning requirements and skill gaps of different groups can be more accurately identified, so that a more personalized and effective training scheme is provided.

It should be understood that the process of human learning is a process of transferring and applying original experience, and deeply processing knowledge as raw materials to convert into self-ability. The final objective of this process is to solve various uncertainty problems. The problem of efficient conversion is faced, whether by migration experience or process knowledge. That is, the process of human learning is not simply to receive and memorize information, but rather to correlate, compare and fuse existing knowledge with new knowledge, thereby building a more complete and profound understanding. Thus, the associative analogy is taken as a learning method, and is based on the cognitive principle that encourages learners to search for internal relations between different knowledge points, and the knowledge migration and application are promoted by deepening understanding through analogy. The essence of learning is to constantly interpret new knowledge with old knowledge, which is a dynamic, continuous process. In this process, the association class can motivate the creativity and imagination of the learner, causing the learner to discover new views and ideas, thereby creating updated, more valuable knowledge. Similarly, the correlation analogy is integrated into training of the flight crew member, so that training efficiency can be improved, criticizing thinking and innovation capability of the flight crew member can be cultivated, and a foundation is laid for personal growth and professional development of the flight crew member.

For training of flight crew members, the embodiment of the application can accurately classify threats and errors, integrate the threats and the errors into high-efficiency training subjects, further construct a training scene library close to actual combat, and is an effective strategy for improving competence and safety performance of the flight crew members.

To this end, embodiments of the present application may learn a hierarchy of threats and errors and then, from the perspective of flight crew members, go to the knowledge, skills and attitudes required to be invoked to manage these threats and errors. And integrating similar knowledge, skills and attitudes to form a modularized training theme.

The process of forming a modular training theme requires special attention:

one is to focus on factor clustering situations of threats and errors. Those factors that are significantly clustered should be considered more important in training, as they tend to occur in complex and difficult contexts. These scenarios may require a higher level of management than simple direct events. In particular, when certain factors are closely related in data analysis or practice and exhibit distinct clustering characteristics, it is often meant that these factors together affect a certain result or phenomenon. During the training process, attention is paid to the factors with remarkable clusters, and the factors are integrated into a single training theme, so that the flight crew can better understand and cope with complex and changeable challenges.

Secondly, the training scenes which can be related to the analogy can be determined through the classification and subclass of the threat and the error and integrated into a training theme. For example, fire or smoke on a flight crew may occur in the form of engine fire, cargo/cabin smoke, classified as warning/no warning, but may also occur in different flight phases, all under the same fire or smoke management theme. Similarly, the present embodiment may specifically set a separate training theme for bird threats and design related scene element paradigms based on the data provided in the data report.

The threat and error classification updates are updated as compared to the prior art. This dynamic change results in the challenge of having to face a rebinning when integrating data. To address this problem, the embodiment of the application may fully comb the threat, error, and TEM model of the UAS and re-plan the respective sub-items. Considering that excessive levels will increase the workload in electronic form use, embodiments of the present application may control all levels to within three and optimize the most common sub-items sequentially. More importantly, the report is classified according to the definitions of threat, error and UAS, so that various operators can collect various data more conveniently and accurately when using TEM tools.

Among other things, classification of threats plays an important role in security management, and therefore, classification thereof generally clusters based on objective properties of events. In contrast, mapped training topics are more training-wise clustered for the knowledge, skills, and attitudes needed to manage these objective threats and errors. Through intensive study of the learning process, the embodiment of the application obtains the conclusion that when the knowledge points form network connection, the memory depth and the understanding strength of the learner are obviously improved compared with the learning effect of the isolated knowledge points. Therefore, training is carried out by adopting clustered training subjects, and the threat and error coping capability can be effectively improved through different conditions under the condition of limited resources.

At the same time, there is a large number of intersections of 28 training topics provided by the prior art. The 28 training topics included both clusters of threats and errors (e.g., bad weather, terrain, wind shear, etc.), competence necessary to address these threats (e.g., workload management, manual handling, automated equipment use, etc.), and division of flight phases (e.g., landing). When each airline company is researched, the set of training subjects are generally fed back to be crisscrossed, and the training effect is poor. In order to improve the training effect, the training subjects are reclassified according to the embodiment of the application, so that operators or course development teams can drive the training efficiency according to data better, and the training effect is maximized.

Based on the use of the safety management method of the flight assembly, the embodiment of the application provides a flight record table of a specific flight unit, which exemplarily comprises the following content of event number XXXXYYZZ for analysis according to time periods of year, month and the like. The time code is FLT2.11-XXXXYYZZ-ZLL-09, the analyst is xxx, the flight phase is approaching, the event label is unstable approaching, the event describes that the runway in a certain area 03 is approaching in a blind way, the field height is about 900 feet, the wind direction and the wind speed are suddenly changed, the flight unit gauge speed is increased to 180 knots, and the flight unit gauge speed exceeds the flap 30 signage speed (175 knots) by 5 knots, and the duration is 1 second. The length of the aircraft reduces the thrust, increases the attitude correction, and does not execute the fly-away. The aircraft length follows the guiding to increase the descending rate and corrects, and the aircraft unit establishes stable approach at 501 feet and falls to the ground normally. During this period, the maximum rate of descent is 1760 feet/minute. The fact and assumption are that weather conditions are affected by typhoons No. 16 "AA", coasts in the southeast have small to medium rain bursts, and short-term heavy rain bursts. The airport in a certain area is 15:00 ATIS, the wind direction is changed between 060 and 130 ℃ at 090℃ and 11 m/s, the visibility is 5 km, the rain is light, the fog is light, the cloud is 1000 feet, the cloud is 2300 feet, the temperature is 26 ℃, and the sea pressure is corrected to 1003 hundred Pa.

The event passes through a airport in a certain area, blind descent approach is carried out by using No. 03 runway, and during the descent preparation period, a set of units makes a treatment plan aiming at wind shear and the influence of precipitation, and the stable approach standard shouting and reminding are emphasized. The flight unit normally establishes blind descent, the field height is 1567 feet, and the captain disconnects the autopilot and the automatic throttle. The field height is about 1000 feet, the gauge speed is 151 knots, the flying unit flies in a precipitation area, the unit turns on a windshield wiper, a captain can visually observe the ground and a runway sequence flashing lamp, and the tower informs the front aircraft that the wind direction and the wind speed change of 700-800 feet are larger. The field height is 906 to 807 feet, the downwind is changed from 10.2 knots to 15.9 knots of top wind, the surface speed of the flight unit is rapidly increased, the copilot reminds that the speed is high, the captain reduces the thrust to slow, and the gesture reduction speed is increased. During this period, the flight crew maximum gauge speed is 180 knots (flap 30 signage speed 175 knots), and the maximum rate of rise is 896 feet per minute. The field height is 884 feet, the flight unit is 1.7 points higher than the glide slope, the copilot reminds that the copilot is 'high', the captain self-thinks that the flight unit can return to the normal vertical section through short-term correction, the copilot can make a decision to continue approaching, and the copilot does not propose objection. The captain maneuvers the flight crew to follow the guideline to increase the descent rate. The field was 807 feet high, 160 knots at a speed of flight, 1760 feet per minute drop, and the flight crew was 1.5 points above the glidepath. The field is 501 feet high, the gauge speed is 161 knots, the descent rate is 1152 feet per minute, the aircraft unit is 0.2 points higher than the glide slope, the field is 396 feet high, the gauge speed is 159 knots, the descent rate is 720 feet per minute, the aircraft unit is 0.7 points lower than the glide slope, and the aircraft unit is normal in the follow-up. During this period, the co-driver does not alert the descent rate. The captain in interview shows that the stabilized approach standard and requirement are known, after the aircraft unit is higher than the glide slope, the attention is focused on follow-up guide correction, the monitoring on the descent rate is ignored, and when the descent rate is found to be large, the aircraft unit is in the normal range of the glide slope, the descent rate is determined to be reduced, the approach is continued, and the missed approach procedure is not executed.

The company conducts declaration and technical discussion on the early unstable approach event through the monthly centralized security education, and the unit participates in and completes training effect verification. The event with high low-altitude descent rate occurs before the company, the branch company qualitatively takes the event as a technical reason in the investigation process, and potential safety hazards of 'the low-altitude descent rate of the unit exceeds the low-altitude descent rate limit' are not identified, so that potential hazard library management is not included.

Low altitude descent rate limit refers to a limit on descent rate for low altitude flights that, unless required by airport programs, should be 2500 to 1000 feet above airport elevation, not greater than 1500 feet per minute, and 1000 feet below airport elevation, not greater than 1000 feet per minute, unless required by programming. The stable approach height requirement is that when the flying unit is 1000 feet away from the runway entrance under the Meter weather condition, when the flying unit is 500 feet away from the runway entrance under the visual weather condition, all simple instructions and inspection sheets should be completed, the flying unit should establish stable approach, and when the flying unit is still unstable approach below the height, the flying unit should immediately start the fly-away procedure.

Stable approach criteria include heading/glide slope guidance and descent rates, where heading and glide slope deviations must be within + -1 point range, and descent rates remain within + -300 feet/minute of the target descent rate. The rate of drop is not greater than 1000 feet/minute. If the expected rate of drop is greater than 1000 feet per minute, a special approach profile should be made. If an unexpected descent rate of greater than 1000 feet/minute is encountered during the approach, a missed approach should be performed, provided that special approach profiles are made and a second approach is attempted.

Also, wind shear strength can be divided into four classes, light, medium, strong, and severe for every 100 feet of altitude wind speed variation range, "severe" meaning wind speed variation exceeding 12 knots. The flight crew increases in pitch 26.1 in the field height 906 to 807 feet of the roof wind component during this start event, encountering severe wind shear.

In the practical application process, wind shear may be encountered (1) indicating airspeed variation over 15 seas, (2) vertical velocity variation over 500 feet/min, and (3) approaching glide slope offset over 1 point in the middle.

Flight data, flight crew full weight 64.2 tons, flap 30, vref147 section, vapp152 section, autopilot and autopilot off, flight guidance on, exemplary flight data may also include (1) 14:23:34, field height 1080 feet, attitude 2.8 degrees, gauge speed 152 section, descent rate 1168 feet/minute, speed percent N1=67%, downwind 3.8 section, flight crew 0.2 points below the glidepath. (2) 14:23:46, field height 906 feet, attitude 1.2 degrees, gauge speed 151 knots, descent rate 1040 feet/min, n1=71%, downwind 10.2 knots, flight crew 0.2 points below the glidepath. (3) 14:23:51, field height 843 feet, attitude 0.7 degrees, gauge speed 169 knots, left side with 3.7 units, descent rate 304 feet/min, n1=55%, top wind 7.1 knots, flight crew lower than the glidepath 0.2 points. (4) 14:23:53, field height 850 feet, attitude 2.8 degrees, speed of flight 180 knots, rate of rise 512 feet per minute, n1=37%, top wind 17.2 knots, flight crew 0.1 points above the glidepath. (5) 14:23:55, field height 879 feet, attitude 3.9 degrees, gauge speed 171 knots, rate of rise 896 feet per minute, n1=31%, top wind 14.4 knots, flight crew 0.8 points above the glidepath. (6) 14:24:01, field height 851 feet, attitude-1.2 degrees, gauge speed 159 knots, descent rate 1216 feet/min, n1=31%, top wind 13.8 knots, flight crew 1.7 points above the glidepath. (7) 14:24:03, field height 807 feet, attitude-1.4 degrees, gauge speed 160 knots, descent rate 1760 feet/min, n1=31%, top wind 15.9 knots, flight crew 1.5 points above the glidepath. (8) 14:24:16, field height 501 feet, attitude-1.9 degrees, gauge speed 161 knots, descent rate 1152 feet/min, n1=40%, top wind 13.2 knots, flight crew on the glidepath. (9) 14:24:23, field height 396 feet, attitude 1.44 degrees, gauge speed 159 knots, descent rate 720 feet/min, n1=33%, top wind 13.6 knots, flight crew 0.7 points below the glidepath. The flight data shows that the maximum airspeed of the flight crew exceeds the flap 30 speed limit by 5 knots for 1 second. And is 1.7 points above the glidepath at maximum. The maximum drop rate of 900-500 feet in field height 1760 feet/min and 501 feet in field height establish a steady approach.

The risk source identification and TEM analysis module can provide the following explanation that the threat is not warning wind shear, the threat management is not found, the threat management can be detection and effective management, the detection and ineffective management are carried out, when the threat is not found, the unit sets a treatment plan aiming at wind shear and rainfall influence, and the treatment plan is emphasized to stably call and remind the user of approaching the standard. Errors include four types of (1) C-communication type errors, namely communication among pilots on the same flight crew, copilot reminding of 'high speed', captain reducing thrust to slow, and increasing gesture reducing speed. The lack of comprehensive monitoring of all current parameters results in incomplete information collection. (2) C-communication errors, namely communication among pilots on the same flight unit, namely that the flight unit is 1.7 points higher than the glide slope, the copilot reminds that the flight unit is 'high', the captain self-thinks that the flight unit can return to a normal vertical section through short-term correction, the decision is made to continue approaching, and the copilot does not propose objection. The incoming UAS (E) is not stable close due to unit errors of the two nodes. (3) P-program error, no flying after unstable approach, that is, after the aircraft length shows that the stable approach standard and requirement are known, the aircraft unit is higher than the glide slope, the attention is focused on follow-up guide correction, the monitoring of the descent rate is ignored, when the descent rate is found to be large, the aircraft unit is in the normal range of the glide slope, the descent rate is reduced, the approach is continued, and no flying procedure is executed. C-communication errors, namely communication among pilots on the same flight crew, namely unstable approach period, and no reminding of the descent rate by the copilot.

In practical application, no detection is made for error (1), no detection is made for error (2), no management is disabled, no detection is made for error (3), and no detection is made for error (4).

The UAS (T) is described as vertical, lateral or speed deviations, field heights 906 to 807 feet, downwind from 10.2 knots to 15.9 knots downwind, and rapid increases in aircraft crew gauge. The UAS (E) is described as unstable approach, field height 807 feet, gauge speed 160 knots, descent rate 1760 feet/minute, and flight crew 1.5 points above the glidepath. If a UAS (T) is detected and is not managed, a specific description is given of a sudden change in the state of the aircraft due to wind shear entering the UAS (T), the crew managing it but returning to the threat management policy due to the threat not being identified, a crew error occurs and this in turn results in entering the UAS (E). If UAS (E) is not detected, a specific description is given that the missed approach procedure is not executed. And (3) ending the state, namely normally landing after unstable approach.

The performance assessment module provides an explanation of the level 2 setting according to the corporate security management policy.

A competence-based module provides an illustration of 1 showing knowledge about physical environments (including humidity, temperature, noise reduction), air traffic environments (including airlines, weather, airports, and operating infrastructure). 2. The energy state of the aircraft is monitored and evaluated, and the predicted flight path is estimated. 3. Communication is suitably upgraded to account for the discovered discrepancies. 4. Deviations from the projected flight path are monitored and identified, and appropriate measures are taken. 5. Exhibit subjective motility and provide guidance when needed. 6. Showing appropriate knowledge about applicable regulations.

Training topics including wind shear change, communication errors, and missed approach management. The training or management scheme provides the following explanation that the training strategy comprises technical discussion, classroom teaching, training and the like, the operation management and control comprises flight timing/cancellation, unit strength collocation, unit technical grade and the like, and the safety strategy comprises unstable approach definition, risk grade definition and the like.

Fig. 3 is a schematic structural diagram of a safety management system of a flight unit according to an embodiment of the present application, where, as shown in fig. 3, the system includes:

A definition module 31 for defining a plurality of risk parameters including a threat, an error, a first undesired aircraft state resulting from the threat, and a second undesired aircraft state resulting from the error, and status parameters including a desired state and an end state, to construct an improved threat and error management TEM model;

The identification module 32 is configured to identify a potential risk source that occurs in the flight unit during the flight process by using a risk source identification algorithm, perform cluster analysis on the potential risk source to obtain a cluster analysis result, and generate a security management policy corresponding to the cluster analysis result according to knowledge, skills and attitudes related to the cluster analysis result, so that the flight unit executes the security management policy and returns to a desired state;

The evaluation module 33 is configured to obtain flight monitoring data generated during the process of executing the safety management policy by the flight crew in the flight crew, and quantitatively evaluate the safety management performance of the flight crew based on the flight monitoring data to obtain an evaluation result;

The determining module 34 is configured to determine training targets and content of the flight crew member according to the evaluation result, so as to perform personalized training on the flight crew member based on the training targets and content, and improve professional skills and team cooperation capability of the flight crew member.

The safety management system of the flight crew described in fig. 3 may execute the safety management method of the flight crew described in the embodiment shown in fig. 1, and its implementation principle and technical effects are not repeated. The specific manner in which the various modules, units, and operations of the safety management system of the aircraft assembly in the above embodiments are performed has been described in detail in connection with the embodiments of the method, and will not be described in detail herein.

In one possible design, the safety management system of the flight crew of the embodiment shown in FIG. 3 may be implemented as a computing device, which may include a storage component 41 and a processing component 42, as shown in FIG. 4.

The storage component 41 stores one or more computer instructions for execution by the processing component 42.

The processing component 42 is configured to define a plurality of risk parameters and state parameters to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include a threat, an error, a first unexpected aircraft state caused by the threat, and a second unexpected aircraft state caused by the error, the state parameters include a desired state and an end state, identify potential risk sources of the aircraft crew during the flight by using a risk source identification algorithm, perform cluster analysis on the potential risk sources to obtain a cluster analysis result, generate a security management policy corresponding to the cluster analysis result according to knowledge, skills and attitudes related to the cluster analysis result, so that the aircraft crew executes the security management policy to restore to the desired state, acquire flight monitoring data generated during execution of the security management policy by the aircraft crew within the aircraft crew, quantitatively evaluate the security management performance of the aircraft crew based on the flight monitoring data to obtain an evaluation result, determine training targets and contents of the aircraft crew based on the evaluation result, perform personalized training on the training targets and contents of the aircraft crew, and improve the professional skills and team capability of the crew.

Wherein the processing component 42 may include one or more processors to execute computer instructions to perform all or part of the steps of the methods described above. Of course, the processing component may also be implemented as one or more Application-specific integrated circuits (ASICs), digital signal processors (DIGITAL SIGNAL processes, DSPs), digital signal processing devices (DIGITAL SIGNAL Process devices, DSPDs), programmable logic devices (Programmable Logic Device, PLDs), field programmable gate arrays (Field Programmable GATE ARRAY, FPGA), controllers, microcontrollers, microprocessors, or other electronic elements for performing the above method.

The storage component 41 is configured to store various types of data to support operations at the terminal. The Memory component may be implemented by any type or combination of volatile or nonvolatile Memory devices such as Random Access Memory (Random Access Memory, RAM), static Random-Access Memory (SRAM), electrically erasable programmable Read-Only Memory (EEPROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), programmable Read-Only Memory (Programmable Read Only Memory, PROM), read Only Memory (ROM), magnetic Memory, flash Memory, magnetic or optical disk.

Of course, the computing device may necessarily include other components as well, such as input/output interfaces, display components, communication components, and the like.

The input/output interface provides an interface between the processing component and a peripheral interface module, which may be an output device, an input device, etc.

The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, and the like.

The computing device may be a physical device or an elastic computing host provided by the cloud computing platform, and at this time, the computing device may be a cloud server, and the processing component, the storage component, and the like may be a base server resource rented or purchased from the cloud computing platform.

The embodiment of the application also provides a computer storage medium which stores a computer program, and the computer program can realize the safety management method of the flight unit in the embodiment shown in the figure 1 when being executed by a computer.

It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, systems and units may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein.

The system embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.

It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application, and not for limiting the same, and although the present application has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present application.

Claims

1. A flight crew safety management method, comprising:

A plurality of risk parameters and state parameters are defined to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include a threat, an error, a first undesirable aircraft state caused by the threat, and a second undesirable aircraft state caused by the error, and the state parameters include a desired state and an end state; the priority of the threat is higher than the priority of the first undesirable aircraft state, and the priority of the second undesirable aircraft state is higher than the priority of the error;

Using a risk source identification algorithm, identify potential risk sources that may occur during flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate safety management strategies corresponding to the cluster analysis results based on the knowledge, skills, and attitudes associated with the cluster analysis results, so that the flight crew can implement the safety management strategies and return to the desired state;

Acquiring flight monitoring data generated during the process of flight crew members executing safety management strategies within the flight crew, and quantitatively evaluating the safety management performance of the flight crew members based on the flight monitoring data to obtain evaluation results;

According to the evaluation results, the training objectives and contents of the flight crew members are determined, so as to provide personalized training to the flight crew members based on the training objectives and contents, so as to improve the professional skills and teamwork ability of the flight crew members.

2. The method according to claim 1, characterized in that the step of generating a safety management strategy corresponding to the cluster analysis results based on the knowledge, skills and attitudes related to the cluster analysis results comprises:

Determine the number of clusters included in the cluster analysis results. One cluster corresponds to one risk parameter, and one risk parameter represents an actual risk source.

If the number of clusters is greater than or equal to two, all actual risk sources corresponding to the cluster analysis results are prioritized according to the nature, impact scope and urgency of the actual risk sources;

According to the priority sorting results, obtain the knowledge, skills and attitudes related to each actual risk source from the knowledge, skills and attitudes related to the cluster analysis results;

According to the knowledge, skills and attitudes related to each actual risk source, the safety management strategy corresponding to each actual risk source is generated to form the safety management strategy corresponding to the cluster analysis result.

3. The method according to claim 2 is characterized in that the threats include predictable threats and unpredictable threats, the errors include associated errors and spontaneous errors, predictable threats and unpredictable threats correspond to different security management strategies, and associated errors and spontaneous errors correspond to different security management strategies.

4. The method according to claim 3 is characterized in that the step of generating a security management strategy corresponding to each actual risk source based on the knowledge, skills and attitudes related to each actual risk source comprises:

For predictable threats, based on the knowledge, skills, and attitudes related to predictable threats, follow the steps in the following process: build an open communication environment, develop a strategic plan, determine the initial strategy based on the strategic plan, divide the tasks in the initial strategy, implement the initial strategy, and make strategic adjustments;

For unpredictable threats, determine whether the crew is calm. If so, perform the following steps in sequence: Based on the knowledge, skills and attitudes related to unpredictable threats and combined with similar historical response experience data, perform flight optimization, navigation planning improvement, communication optimization, and threat factor identification and management;

For correlated errors, combine the knowledge, skills and attitudes related to correlated errors, conduct self-error management by setting designated short-term goals in specific scenarios, and conduct error management of other flight crew members through direct statement method;

For spontaneous errors, combine the knowledge, skills and attitudes related to related errors, conduct self-error management by setting personal short-term goals, and manage the errors of other flight crew members through direct statement method;

For the first undesirable aircraft state, three strategies, namely, stop, return and escape, are used to restore the flight crew to the desired state;

For the second undesirable aircraft state, three strategies, namely stop, return and escape, are used to restore the flight crew to the desired state, and then error management is performed.

5. The method according to claim 4, characterized in that the knowledge, skills and attitudes related to unpredictable threats are combined with similar historical response experience data to perform flight optimization, navigation planning improvement, communication optimization, threat factor identification and management, including:

According to the location, time and impact range of unpredictable threats, the nearest neighbor algorithm is used to obtain historical response experience data similar to unpredictable threats from the historical database;

Based on the knowledge, skills and attitudes related to unpredictable threats, reinforcement learning algorithms are used to dynamically adjust similar historical response experience data to obtain safety management strategies corresponding to unpredictable threats. Based on the safety management strategies corresponding to unpredictable threats, flight optimization, navigation planning improvements, communication optimization, and threat factor identification and management are carried out.

6. The method according to claim 1, characterized in that the quantitative evaluation of the safety management performance of the flight crew members based on the flight monitoring data to obtain the evaluation results comprises:

Dividing the flight monitoring data according to different flight phases to obtain specific data for each flight phase, wherein the flight phase includes take-off, cruising and landing;

For each flight phase, set corresponding evaluation indicators, which include at least one of the following: flight parameter deviation, operation response time, task completion and team collaboration effect;

Based on the specific data of each flight phase, calculate the scores of the flight crew members for the corresponding evaluation indicators in each flight phase;

Compare the scores of the evaluation indicators corresponding to each flight phase of the flight crew members with the preset safety management performance standards corresponding to each flight phase, and obtain the comparison results of the evaluation indicators corresponding to each flight phase of the flight crew members. The comparison results are performance levels, and different flight phases correspond to different preset safety management performance standards;

A performance evaluation report of the flight crew member is generated according to the comparison result, and the performance evaluation report is used as the evaluation result.

7. The method according to claim 6, characterized in that determining the training objectives and contents of the flight crew members according to the evaluation results comprises:

According to the evaluation results, identify the weak links and skills to be improved of the flight crew members during the flight process, wherein the skills to be improved are evaluation indicators whose performance levels do not meet the preset level requirements, and the weak links are flight stages corresponding to the evaluation indicators whose performance levels do not meet the preset level requirements;

According to the weak links and skills to be improved, corresponding training topics are selected from the preset training topic library, and the training topics include at least one of the following: wind shear recovery, communication errors and go-around management;

Determine personalized training objectives based on the training theme, design training contents based on the training objectives, determine designated training methods based on the habitual characteristics of flight crew members, and use the designated training methods to present the training contents, the training methods include theoretical training and simulator training, the training objectives include at least one of the following: improve the accuracy of flight operations, enhance emergency response capabilities, prevent omissions of flight missions, and improve teamwork capabilities; the training contents include at least one of the following: simulated flight training, emergency scenario drills, enhanced task list management, and teamwork training.

8. A safety management system for a flight crew, comprising:

A definition module, used for defining a plurality of risk parameters and state parameters to construct an improved threat and error management TEM model, wherein the plurality of risk parameters include a threat, an error, a first undesirable aircraft state caused by the threat, and a second undesirable aircraft state caused by the error, and the state parameters include an expected state and an end state; the priority of the threat is higher than the priority of the first undesirable aircraft state, and the priority of the second undesirable aircraft state is higher than the priority of the error;

An identification module is used to use a risk source identification algorithm to identify potential risk sources that may occur during flight, perform cluster analysis on the potential risk sources, obtain cluster analysis results, and generate a safety management strategy corresponding to the cluster analysis results based on knowledge, skills, and attitudes related to the cluster analysis results, so that the flight crew can execute the safety management strategy and return to a desired state;

An evaluation module, used to obtain flight monitoring data generated during the process of flight crew members in the flight crew executing the safety management strategy, and to quantitatively evaluate the safety management performance of the flight crew members based on the flight monitoring data to obtain an evaluation result;

The determination module is used to determine the training objectives and content of the flight crew members according to the evaluation results, so as to provide personalized training to the flight crew members based on the training objectives and content, and improve the professional skills and teamwork ability of the flight crew members.

9. A computing device, characterized in that it comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a flight crew safety management method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that a computer program is stored therein, and when the computer program is executed by a computer, the flight crew safety management method according to any one of claims 1 to 7 is implemented.