CN119929672B - A safe operation control system for mining monorail crane based on the Internet of Things - Google Patents
A safe operation control system for mining monorail crane based on the Internet of ThingsInfo
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- CN119929672B CN119929672B CN202510287451.6A CN202510287451A CN119929672B CN 119929672 B CN119929672 B CN 119929672B CN 202510287451 A CN202510287451 A CN 202510287451A CN 119929672 B CN119929672 B CN 119929672B
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
本发明公开了一种基于物联网的矿用单轨吊安全运行控制系统，本发明涉及单轨吊安全运行监测技术领域，解决了单纯采集工作参数，无法深度对比分析判断设备真实工作状态，却缺乏针对性的后续控制策略的技术问题，本发明通过创新性设立单轨吊参数采集单元，能实时、精准抓取设备全维度工作参数，并利用参数比较分析单元，对照操作人员基于过往丰富记录设定的正常参数区间，迅速、精准判断设备工作状态，融合地理信息系统与高精度定位技术，对轨道路线途经区域智能分类，依据区域平均人流量动态调整运行策略，异常情况分析单元突破传统单一警报模式，深挖异常参数关联因素，计算风险值，结合周期变化灵活决策，当风险值超阈值，立即停机。
The present invention discloses a mining monorail crane safety operation control system based on the Internet of Things. The present invention relates to the technical field of monorail crane safety operation monitoring, and solves the technical problem of simply collecting working parameters, being unable to conduct in-depth comparative analysis to determine the actual working status of the equipment, and lacking a targeted subsequent control strategy. The present invention innovatively establishes a monorail crane parameter collection unit, which can accurately capture the full-dimensional working parameters of the equipment in real time, and utilizes a parameter comparison and analysis unit to quickly and accurately determine the working status of the equipment by comparing the normal parameter range set by the operator based on rich past records. The present invention integrates geographic information systems and high-precision positioning technologies, intelligently classifies the areas passed by the track route, and dynamically adjusts the operation strategy according to the average passenger flow in the area. The abnormal situation analysis unit breaks through the traditional single alarm mode, deeply explores the correlation factors of abnormal parameters, calculates risk values, and makes flexible decisions based on periodic changes. When the risk value exceeds the threshold, the equipment is shut down immediately.
Description
Technical Field
The invention relates to the technical field of monitoring of safe operation of monorail cranes, in particular to a mining monorail crane safe operation control system based on the Internet of things.
Background
In the industrial fields of mineral exploitation and the like, the monorail crane becomes a key transportation device in a well or a large factory workshop by virtue of the efficient material transportation and personnel carrying capacity. However, the working environment of the monorail crane is often complex and changeable, and is full of a plurality of potential safety hazards.
According to publication number CN117566600B, a mining monorail crane safe operation control system based on the Internet of things is disclosed, and comprises the steps of identifying whether each deformation position is an acceleration point position or not through analyzing the deformation degree of each deformation position on a sliding track structure, analyzing the running blocking coefficient of each deformation position of the sliding track structure, and further analyzing the real-time operation health coefficient of the sliding track structure through identifying whether foreign matters exist on the track operation structure. By detecting the running temperature measurement index of each pulley bracket on the mining monorail crane in real time, the real-time running safety coefficient of the pulley structure is analyzed, and whether the parking mode is started or not is further confirmed. And (3) by identifying the outline shape of each load, evaluating the shaking distance of the load at each acceleration point, and determining the shaking direction of each load, so as to analyze whether collision risks exist between the loads.
However, the traditional single-rail overhead crane line management is dependent on manual inspection and experience judgment, operators need to check the state and the track condition of equipment in a fixed time and on site, labor intensity is high, efficiency is low, and moreover, real-time and accurate control of the operation parameters of the equipment is difficult to realize by manpower, and once the emergency such as abnormal operation speed, overheat and overload of the equipment occurs, the emergency is difficult to timely detect and treat, so that the occurrence probability of safety accidents is greatly increased.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a mining monorail crane safe operation control system based on the Internet of things, which solves the problems that the working parameters are simply collected, the real working state of equipment cannot be judged by deep comparison analysis, and a targeted follow-up control strategy is lacking.
In order to achieve the purpose, the invention is realized through the following technical scheme that the mining monorail crane safe operation control system based on the Internet of things comprises:
The parameter comparison analysis unit is used for analyzing the working parameters of the monorail crane transmitted by the monorail crane parameter acquisition unit, identifying the working state of the monorail crane by comparing the working parameters, and generating a state identification result, wherein the state identification result comprises a normal working state and an abnormal working state, transmitting the normal working state to the normal condition analysis unit and transmitting the abnormal working state to the abnormal condition analysis unit;
The normal condition analysis unit is used for analyzing the acquired normal working state, judging the passing area of the monorail crane, judging the risk of the passing area to generate a risk judgment result, simultaneously analyzing the risk judgment result by combining the historical data to generate operation control information, and transmitting the operation control information to the control information output unit;
The abnormal condition analysis unit is used for analyzing the acquired abnormal working state, analyzing the abnormal working parameters, carrying out risk prediction by combining the corresponding associated parameters to generate a prediction result, analyzing the prediction result based on the periodic variation of the abnormal parameters, generating operation control information and transmitting the operation control information to the control information output unit.
As a further scheme of the invention, the system also comprises a monorail crane parameter acquisition unit and a control information output unit;
The monorail crane parameter acquisition unit is used for acquiring working parameters of the monorail crane in a working state and transmitting the acquired working parameters to the parameter comparison analysis unit;
And the control information output unit is used for displaying the acquired operation control information to the corresponding operator.
As a further scheme of the invention, the specific mode of the parameter comparison and analysis unit for analyzing the working parameters of the monorail crane is as follows:
and (3) acquiring the working parameters of the monorail crane, and simultaneously acquiring the normal working parameters of the monorail crane, and matching the working parameters of the monorail crane with the normal working parameters, wherein if the working parameters of the monorail crane are matched with the normal working parameters, the working state of the monorail crane is normal, and a normal working state result is generated, otherwise, if the working parameters of the monorail crane are not matched with the normal working parameters, the working state of the monorail crane is abnormal, and an abnormal working state result is generated.
As a further scheme of the invention, the specific mode of the normal condition analysis unit for analyzing the normal working state is as follows:
Acquiring a track route of a monorail crane, acquiring and marking a region passing through the track route as a passing region i, wherein i=1, 2, & gt, j represents the number and the number of the passing regions, judging the risk of the passing region i, classifying the passing region as a dangerous passing region correspondingly if the passing region has the risk, and classifying the passing region as a normal passing region correspondingly if the passing region has no risk;
And carrying out normal monitoring on the normal passing area, generating normal monitoring information, generating a secondary analysis signal on the dangerous passing area, and processing the secondary analysis signal.
As a further aspect of the present invention, the specific manner in which the normal condition analyzing unit processes the secondary analysis signal is:
And acquiring the classified dangerous passing areas, simultaneously acquiring the average people flow of the dangerous passing areas, comparing the calculated average people flow with a preset value, if the average people flow is larger than the preset value, indicating that the people flow of the dangerous passing areas is larger, generating parking control information, otherwise, if the average people flow is smaller than the preset value, indicating that the people flow of the dangerous passing areas is normal, generating a deceleration signal, and analyzing the generated deceleration signal.
As a further aspect of the present invention, the specific manner in which the normal condition analyzing unit analyzes the deceleration signal is:
Acquiring historical data, simultaneously acquiring a historical record similar to the average human flow in the current dangerous passing area in the historical data, acquiring a corresponding running speed in the historical record, calculating an average value of the running speeds to be recorded as a standard value, simultaneously acquiring a real-time running speed, and comparing the real-time running speed with the standard value;
and if the real-time running speed is larger than the standard value, regulating the real-time running speed with the standard value and generating differential control information, otherwise, if the real-time running speed is smaller than the standard value, keeping the real-time running speed and generating normal running information.
As a further aspect of the present invention, the specific manner in which the abnormal condition analyzing unit analyzes the abnormal operating state is:
Acquiring working parameters corresponding to abnormal working states and recording the working parameters as abnormal working parameters, acquiring associated parameters of the abnormal working parameters based on historical data, calculating relation indexes of the associated parameters and the abnormal working parameters, then carrying out risk level identification on the abnormal working parameters, assigning the obtained risk level, processing the associated parameters in the same way, and substituting the obtained parameters into a formula Calculating to obtain a risk value R of the abnormal working parameters, wherein w n represents the weight of n abnormal working parameters, p n is the risk grade assignment of the abnormal working parameters, H n is the associated parameter weight of the abnormal working parameters,Is a relationship index;
And comparing the calculated risk value with a threshold value, generating stop information if the risk value is larger than the threshold value, and generating and analyzing a periodic variation monitoring signal if the risk value is smaller than the threshold value.
As a further aspect of the present invention, the specific manner in which the abnormal situation analysis unit analyzes the periodic variation monitoring signal is:
And acquiring a change value of the abnormal working parameter in the time period T, acquiring a change value corresponding to the associated parameter, substituting the acquired change value into a risk value calculation formula to calculate a periodic change risk value, comparing the periodic change risk value with a threshold value, generating stop information if the periodic change risk value is larger than the threshold value, and otherwise, generating periodic monitoring information if the periodic change risk value is smaller than the threshold value.
The invention provides a mining monorail crane safe operation control system based on the Internet of things. Compared with the prior art, the method has the following beneficial effects:
The invention can grasp the full-dimension working parameters of the equipment in real time and accurately by innovatively setting the parameter acquisition unit of the monorail crane, and by utilizing the parameter comparison analysis unit, the working state of the equipment is rapidly and accurately judged by contrasting the normal parameter interval set by operators based on the past rich records, the geographical information system and the high-precision positioning technology are fused, the passing areas of the track route are intelligently classified, the dangerous and normal areas are accurately distinguished, and the operation strategy is dynamically adjusted according to the average people flow of the areas;
the abnormal condition analysis unit breaks through the traditional single alarm mode, deep digs abnormal parameter association factors, calculates a risk value, combines periodic variation to flexibly decide, immediately stops when the risk value exceeds a threshold value, continuously monitors when the risk value does not exceed the threshold value, and adjusts according to working conditions in real time.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention.
Detailed Description
The following description of the embodiments of the present invention 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 invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the application provides a mining monorail crane safe operation control system based on the internet of things, which comprises a monorail crane parameter acquisition unit, a parameter comparison analysis unit, an abnormal situation analysis unit, a normal situation analysis unit and a control information output unit, wherein the functional units are in unidirectional electrical connection with each other as can be known from the accompanying drawings.
And the monorail crane parameter acquisition unit is used for acquiring working parameters of the monorail crane in a working state and transmitting the acquired working parameters to the parameter comparison analysis unit, wherein the working parameters comprise parameters such as running speed, position, load, equipment temperature and the like.
And the parameter comparison and analysis unit is used for analyzing the acquired working parameters of the monorail crane, identifying the working state of the monorail crane by comparing the working parameters, and generating a state identification result, wherein the state identification result comprises a normal working state and an abnormal working state, transmitting the normal working state to the normal condition analysis unit and transmitting the abnormal working state to the abnormal condition analysis unit.
The method comprises the steps of obtaining working parameters of the monorail crane, obtaining normal working parameters of the monorail crane at the same time, setting the normal working parameters by an operator according to a past working record, setting the normal working parameters to be interval values, for example, setting a normal running speed interval of the monorail crane to be 5-8 m/s, setting a normal working temperature interval of a motor to be 50-70 ℃, setting a normal load weight interval to be 1-3 tons, setting a normal braking pressure interval to be 2-4 megapascals, matching the working parameters of the monorail crane with the normal working parameters, if the working parameters are matched, indicating that the working state of the monorail crane is normal, and generating a normal working state result, otherwise, indicating that the working state of the monorail crane is abnormal, generating an abnormal working state result, and indicating that all parameters are located in the normal working parameter interval when any group of parameters are not located in the normal working parameter interval, and indicating that the parameters are not matched.
Assuming that the running speed of the monorail crane is 6.5 m/s currently obtained, the temperature of the motor is 60 ℃, the load weight is 2 tons, and the braking pressure is 3 megapascals, the parameters are all in the corresponding normal working parameter intervals, the working state of the monorail crane can be judged to be normal, otherwise, if the running speed of the obtained monorail crane is 9 m/s and exceeds the normal running speed interval, or the temperature of the motor reaches 80 ℃, and any one or more working parameters such as the temperature higher than the normal temperature interval are not in the normal interval range, the working state of the monorail crane is abnormal.
And the normal condition analysis unit is used for analyzing the acquired normal working state, judging the passing area of the monorail crane, judging the danger of the passing area to generate a danger judgment result, simultaneously analyzing the danger judgment result by combining the historical data to generate operation control information, and transmitting the operation control information to the control information output unit.
The method comprises the steps of obtaining a track route of a monorail crane, meanwhile, obtaining and marking a passing area i of the track route, wherein i=1, 2, and j, j represents the number of the passing areas, and accurately obtaining track route information of the monorail crane by means of a high-precision positioning and mapping technology. When a track route is acquired, each area through which the track route passes is acquired and identified in detail by using a Geographic Information System (GIS) or special area identification software, then the risk of a passing area i is judged, if the passing area has a risk, the passing area is correspondingly classified as a dangerous passing area, otherwise, if the passing area does not have a risk, the passing area is correspondingly classified as a normal passing area, normal monitoring is carried out for the normal passing area, normal monitoring information is generated, a secondary analysis signal is generated for the dangerous passing area, and the secondary analysis signal is processed;
for example, for the passing area 1, if the area is located in a workshop with frequent personnel activities and relatively narrow space, the past accident record shows that a collision accident occurs, and if some temporarily placed obstacles exist in the area, the passing area can be judged to be dangerous according to the factors, and classified as a dangerous passing area, and for the passing area 3, the area is a special transportation channel with wide and good vision, no obvious obstacle exists, no other interference factors exist in the periphery, no safety accident occurs in the past, and the passing area is judged to be not dangerous, and is classified as a normal passing area.
Acquiring classified dangerous passing areas, acquiring average people flow of the dangerous passing areas at the same time, acquiring the average people flow by calculating the people flow of different time periods in working time, for example, dividing time period into 1 hour, dividing one day to obtain 24 periods, acquiring corresponding working time periods at the same time, calculating corresponding people flow, finally summing the calculated people flow of all periods to calculate an average value, comparing the calculated average people flow with a preset value, setting a specific numerical value of the preset value by an operator, specifically, calculating the people flow corresponding to the occurrence times of accidents in past history data, if the average people flow is larger than the preset value, indicating that the people flow of the dangerous passing areas is larger, generating parking control information, otherwise, indicating that the people flow of the dangerous passing areas is normal, generating a deceleration signal, and analyzing the generated deceleration signal;
And acquiring historical data, simultaneously acquiring a historical record similar to the average human flow in the current dangerous passing area in the historical data, acquiring a corresponding running speed in the historical record, calculating an average value of the running speeds, recording the average value as a standard value, simultaneously acquiring a real-time running speed, comparing the real-time running speed with the standard value, regulating the real-time running speed with the standard value if the real-time running speed is larger than the standard value, generating differential control information, otherwise, keeping the real-time running speed and generating normal running information if the real-time running speed is smaller than the standard value.
Taking a monorail crane transportation system in a certain factory as an example, the current monorail crane is about to drive into a dangerous passing area, namely a maintenance workshop passageway, the area is frequently provided with equipment and parts for carrying by shuttling and moving by workers, the average human flow rate is dynamically changed, the average human flow rate is 60 people/min after 30 minutes is measured by an infrared human flow rate monitor at the entrance of the workshop, the system rapidly searches and matches in a historical database, historical records of 5 sections of similar human flow rate time periods are screened out, the running speed of the corresponding monorail crane is sequentially 3.5m/s, 3.7m/s, 3.6m/s, 3.4m/s and 3.8m/s, the standard value is calculated to be about 3.6m/s, at the moment, the speed sensor feedback real-time running speed on the monorail crane is 4.0m/s and is greater than the standard value, the intelligent speed regulating system is started immediately, and the PID controller rapidly calculates a motor speed reducing instruction according to the speed deviation (4.0-3.6=0.4 m/s), so that the speed of the monorail crane is steadily reduced, and the speed reaches 3.6m/s after 3.6 s is regulated.
And combining the obtained differential control information and the normal running information to obtain running control information, and transmitting the running control information to a control information output unit.
And the control information output unit is used for displaying the acquired operation control information to the corresponding operator.
Embodiment two, which is an embodiment two of the present invention, is implemented on the basis of embodiment one and differs from embodiment one in that:
And the abnormal condition analysis unit is used for analyzing the acquired abnormal working state, analyzing the abnormal working parameters, carrying out risk prediction by combining the corresponding associated parameters to generate a prediction result, and simultaneously analyzing the prediction result based on the periodic change of the abnormal parameters to generate operation control information.
Acquiring working parameters corresponding to abnormal working states and recording the working parameters as abnormal working parameters, acquiring associated parameters of the abnormal working parameters based on historical data, wherein the associated parameters represent data changing along with the change of the abnormal working parameters, calculating a relation index of the associated parameters and the abnormal working parameters, carrying out risk grade identification on the abnormal working parameters, assigning the obtained risk grade, processing the associated parameters in the same way, and substituting the obtained parameters into a formulaCalculating to obtain a risk value R of the abnormal working parameters, wherein w n represents the weight of n abnormal working parameters, p n is the risk grade assignment of the abnormal working parameters, H n is the associated parameter weight of the abnormal working parameters,Is a relationship index;
comparing the calculated risk value with a threshold value, setting a specific value of the threshold value by an operator, if the risk value is larger than the threshold value, indicating that the abnormal working parameter risks the whole work of the monorail crane, generating stop information, and if the risk value is smaller than the threshold value, indicating that the abnormal working parameter does not risk the whole work of the monorail crane, and generating a periodic variation monitoring signal;
Acquiring a change value of an abnormal working parameter in a time period T, simultaneously acquiring a change value corresponding to an associated parameter, substituting the acquired change value into a risk value calculation formula to calculate a periodic change risk value, wherein the risk value calculation formula is the same as the formula, comparing the periodic change risk value with a threshold value, generating stop information if the periodic change risk value is larger than the threshold value, and otherwise, generating periodic monitoring information if the periodic change risk value is smaller than the threshold value;
and combining the obtained stop information and the period monitoring information to obtain operation control information, and transmitting the operation control information to a control information output unit.
And the control information output unit is used for displaying the acquired operation control information to the corresponding operator.
Embodiment III the present invention is directed to combining the implementation of embodiment I and embodiment II.
Some of the data in the above formulas are numerical calculated by removing their dimensionality, and the contents not described in detail in the present specification are all well known in the prior art.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (6)
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| CN117893193A (en) * | 2023-12-26 | 2024-04-16 | 淮北矿业传媒科技有限公司 | A monorail crane fault inspection and repair system and method |
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| US8907608B2 (en) * | 2011-05-24 | 2014-12-09 | Overhead Door Corporation | Predictive thermal protection for motors in barrier operator systems |
| CN115372932A (en) * | 2022-07-08 | 2022-11-22 | 中国矿业大学 | System and method for evaluating driveability of monorail crane and predicting roadway risk |
| CN116946225B (en) * | 2023-07-31 | 2024-08-13 | 尤洛卡（山东）矿业科技有限公司 | Abnormal information processing method and system for monorail crane |
| CN117086864B (en) * | 2023-08-02 | 2024-02-27 | 上海迪成智能科技有限公司 | Inspection robot safety fault accurate positioning method for monorail crane operation |
| CN118619117A (en) * | 2024-06-26 | 2024-09-10 | 安徽路特威智能机械工程有限公司 | An adaptive driving system for monorail crane |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117893193A (en) * | 2023-12-26 | 2024-04-16 | 淮北矿业传媒科技有限公司 | A monorail crane fault inspection and repair system and method |
| CN118419788A (en) * | 2024-07-05 | 2024-08-02 | 山东济矿鲁能煤电股份有限公司阳城煤矿 | Intelligent control system for approaching protection and anti-collision protection of monorail crane personnel |
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