CN115689399B - Rapid construction method of hydropower equipment information model based on industrial Internet platform - Google Patents
Rapid construction method of hydropower equipment information model based on industrial Internet platform Download PDFInfo
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Abstract
A hydropower equipment information model rapid construction method based on an industrial Internet platform comprises the following steps: and 1, constructing a logic device hierarchical structure based on the hydroelectric device. And 2, constructing an instantiated hydropower equipment hierarchical model. And 3, constructing a hydropower equipment code based on the KKS coding rule and the original equipment asset code. And 4, constructing a panoramic information model of various data of the hydroelectric equipment based on KKS codes and data association relations. The invention solves the problem of data information integration among and in different hydropower enterprises, different hydropower stations through a unified data structure model, opens up a data island, and lays a foundation for realizing large data application of the hydropower enterprises.
Description
Technical Field
The invention belongs to the technical field of industrial Internet in the hydropower industry, and particularly relates to a hydropower equipment information model rapid construction method based on an industrial Internet platform.
Background
A large amount of data can be generated in the production operation process of the traditional hydropower enterprises, wherein the data comprise real-time data of industrial sensors in the production field, structured data and unstructured data in the service management field, but the data are distributed in all subsystems, interconnection and intercommunication cannot be guaranteed, sharing cannot be carried out, value excavation and utilization cannot be effectively carried out, and waste of data resources is caused. With the development of the hydropower industry in China, more and more applications face scenes such as cross-system interaction, cross-life cycle, external data sharing, comprehensive statistical decision and the like. However, the data required for these scenes are cluttered, scattered, and difficult to be utilized in a fusion manner, and the following typical problems exist: the data are not known: large amounts of data have been formed, but the data resources are unclear; data are not desirable: the system is dispersed to form an information island, so that sharing is difficult; data is not available: the data quality is low, statistics is inaccurate, and the data is diversified; data management has no planning: an effective management mode is not formed, and the data standards are not uniform; the security of data is difficult to guarantee: the shared backup mechanism is not sound; data are difficult to analyze: the data is not effectively utilized, and powerful support cannot be provided for a decision maker, etc.
Therefore, on the basis of original automation and informatization, unified equipment data modeling is adopted, multi-source heterogeneous data such as real-time domain data and management domain data are produced in a deep fusion mode, all the data are unified and managed, and meanwhile, the data are fused with model information, so that various high-level application requirements of a hydropower station are met, and a unified digital equipment object is constructed.
Disclosure of Invention
In view of the technical problems existing in the background technology, the hydropower equipment information model rapid construction method based on the industrial Internet platform provided by the invention adopts unified equipment data modeling aiming at hydropower equipment, deeply fuses and produces multi-source heterogeneous data such as real-time domain data and management domain data, uniformly nanotubes all the data, and fuses with model information at the same time so as to meet various high-level application requirements of hydropower stations.
In order to solve the technical problems, the invention adopts the following technical scheme:
a hydropower equipment information model rapid construction method based on an industrial Internet platform comprises the following steps:
Step 1, constructing a logic device hierarchical structure based on hydroelectric devices: the hydropower equipment is constructed into a multi-level set of general logic equipment hierarchical structures according to the containing relations of the system, the subsystem and the components, and the logic equipment hierarchical structures need to contain all types of similar equipment;
step 2, constructing an instantiated hydropower equipment hierarchical model: firstly, manually constructing KKS coding data based on KKS coding rules, and mapping the KKS coding data with the logic equipment level obtained in the step 1 to form a complete instantiation hydropower equipment level model, wherein each node in the hydropower equipment level model has only unique KKS codes corresponding to the nodes;
Step 3, constructing a hydropower equipment code based on a KKS coding rule and an original old equipment code; acquiring an equipment coding data set A s={A1,…,An of original old equipment by using an information extraction mode, and manually constructing an equipment KKS coding data set KKS= { K 1,…,Kn } based on a KKS coding rule, wherein A n is an asset code of nth equipment, and K n is a KKS code of nth equipment; combining the device KKS code and the old device code to form a new double code C new={[ K1, A1],…[ Kn, An of the device, and forming a new double code data set of the device; mapping and matching the new double code C new with the existing old equipment code A s to realize one-to-one mapping of the old equipment tree and the new equipment tree;
step 4, constructing a panoramic information model of various data of the hydroelectric equipment based on KKS codes and data association relations; the panoramic information comprises static information, dynamic information, knowledge and analysis methods of the hydroelectric equipment.
Preferably, in step 4, the static information includes various types of information which are endowed by the equipment factory including equipment factory information, inherent attributes and inherent parameters and cannot change along with the running state of the equipment.
Defining an original coding data set of static information as T ( Static state )={T( Static state )1,…, T( Static state )n, wherein T ( Static state )n represents original coding of an nth piece of static information; static information data set K （ Static state ） of the device is constructed based on KKS coding and data association relation, and the expression is as follows:
K（ Static state ）={K（ Static state ）1,…,K（ Static state ）n}；
Wherein, K （ Static state ）n=[Kn+T( Static state )n ];
K （ Static state ）n represents: coding static information data of an nth device;
K n represents: KKS encoding of the nth device;
T ( Static state )n represents: original encoding of the nth static information;
the static information data code K （ Static state ）n of the nth device can be obtained through the combination of the T ( Static state )n and the K n, and the association between the device and the static information data can be realized rapidly;
the corresponding relation between the static information and the equipment is as follows: one device or component is mapped with a plurality of different pieces of static information, and one piece of static information can also be mapped with a plurality of similar devices or components.
Preferably, in step 4, the dynamic information includes real-time data generated in the running process of the device and result data generated by processing the real-time data, and the data changes along with the running or state change of the device, and is measured by various monitoring devices and sensors.
Defining an original coding data set of the dynamic information as T ( Dynamic state )={T( Dynamic state )1,…, T( Dynamic state )n, wherein T ( Dynamic state )n represents the original coding of the nth piece of dynamic information; dynamic information data set K （ Dynamic state ） of the device is constructed based on KKS coding and data association relation, and the expression is as follows:
K（ Dynamic state ）={K（ Dynamic state ）1,…,K（ Dynamic state ）n}；
wherein, K （ Dynamic state ）n=[Kn+T( Dynamic state )n ];
k （ Dynamic state ）n represents: coding dynamic information data of an nth device;
K n represents: KKS encoding of the nth device;
t ( Dynamic state )n represents: original coding of the nth dynamic information;
The dynamic information data code K （ Dynamic state ）n of the nth device can be obtained through the combination of the T ( Dynamic state )n and the K n, and the association between the device and the dynamic information data can be realized rapidly;
the correspondence between the dynamic information and the device is that one device or component is mapped with a plurality of dynamic information, but one dynamic information is mapped with only one device or component.
Preferably, in step 4, the knowledge includes various knowledge precipitates related to the operation and maintenance of the equipment or the component, including fault cases, mechanism models, overhaul and maintenance rules and various standards formed in the operation and maintenance of the equipment, and the knowledge also includes multidimensional heterogeneous data such as structured data, unstructured data and the like;
defining an original encoding dataset of knowledge as T ( Knowledge of )={T( Knowledge of )1,…, T( Knowledge of )n, wherein T ( Knowledge of )n represents an original encoding of the nth knowledge; knowledge data set K （ Knowledge of ） of the device is constructed based on KKS coding and data association relation, and the expression is:
K（ Knowledge of ）={K（ Knowledge of ）1,…,K（ Knowledge of ）n}；
wherein, K （ Knowledge of ）n=[Kn+T( Knowledge of )n ];
k （ Knowledge of ）n represents: knowledge data encoding of the nth device;
K n represents: KKS encoding of the nth device;
T ( Knowledge of )n represents: original encoding of the nth knowledge;
Through the combination of the T ( Knowledge of )n and the K n, the knowledge data code K （ Knowledge of ）n of the nth device can be obtained, and the association between the device and the knowledge data can be realized rapidly;
the correspondence between the knowledge and the device is mapping between one device or component and a plurality of pieces of knowledge.
Preferably, in step 4, the analysis method includes a conventional analysis method and algorithm, and further includes various rules, indexes and algorithms such as various big data analysis methods and algorithms;
Defining an analysis method original coding data set as T ( Method of )={T( Method of )1,…, T( Method of )n, wherein T ( Method of )n represents original coding of an nth method; the expression of the data set K （ Method of ） of the method for constructing the equipment based on the KKS code and the data association relation is as follows:
K（ Method of ）={K（ Method of ）1,…,K（ Method of ）n}；
wherein, K （ Method of ）n=[Kn+T( Method of )n ];
k （ Method of ）n represents: data encoding of the method of the nth device;
K n represents: KKS encoding of the nth device;
T ( Method of )n represents: original encoding of the nth method;
By combining the T ( Method of )n with the K n, the data code K （ Method of ）n of the method of the nth device can be obtained, and the association of the device and the method can be realized quickly;
The corresponding relation between the instantiated analysis method K （ Method of ） and the equipment is one-to-one mapping.
Preferably, the KKS codes in the panoramic information model of various data of the hydroelectric equipment constructed in the step 4 are extracted, the KKS codes are mapped with the instantiation hydroelectric equipment hierarchical model constructed in the step 2 one by one, the formed mapping results are sorted by taking the equipment as the center, and the panoramic information model taking the equipment as the center is formed.
The following beneficial effects can be achieved in this patent:
1. the invention can integrate the hydropower equipment information again by taking the research object as the center, and reasonably manage all the information surrounding the equipment object, so that a user can regularly, batchly and comprehensively acquire data in the process of using the data, thereby improving the sharing and application efficiency of the user to the data and the model.
2. The invention provides a method for carrying out association fusion on hydropower equipment and an information model thereof, which realizes fusion of data information of the hydropower equipment, constructs a unified digital equipment object and meets the high-level application requirements of a hydropower enterprise industrial Internet platform.
Drawings
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
FIG. 1 is a flow for quickly constructing an information model of hydroelectric equipment;
Fig. 2 is a panoramic information model of the hydro-generator set of the present invention.
Detailed Description
Example 1:
The invention unifies the information models of the hydropower equipment in the industrial Internet, constructs the equipment, the information, the knowledge and the analysis method by taking the equipment as a center, solves the scattered and disordered problems between the hydropower equipment and the information, the knowledge and the analysis method, realizes the complete association and integration of the equipment and the related information, knowledge and analysis method, and solves the scattered problem of industry data. The patent introduces an object-oriented thought to the hydroelectric equipment for the first time, and provides a method for constructing a panoramic information model around the hydroelectric equipment; the traditional three-range data modeling has no clear object and center, is complex to implement, has an undefined theme, and is not intuitive when providing data services. The model considers the analysis methods such as an algorithm model, a rule model and index processing for the first time, and the traditional equipment information model only considers the data. Taking a hydroelectric generating set as an example, the method and the process for quickly constructing the information model are as follows.
Step 1, constructing a logic device hierarchical structure based on hydroelectric devices: the hydropower equipment is constructed into a multi-level set of general logic equipment hierarchical structures according to the containing relations of the system, the subsystem and the components, and the logic equipment hierarchical structures need to contain all types of similar equipment;
For example: and constructing a logic device hierarchical structure based on the hydroelectric generating set, and constructing the hydroelectric generating set into a set of multi-level general logic device hierarchical structures of the hydroelectric generating set according to the inclusion relation of the system, the subsystem and the components, wherein the logic device hierarchical structure needs to contain all types of the hydroelectric generating set as shown in a table 1.
Table 1 logical device hierarchy construction table for water turbine generator set
Step 2, constructing an instantiated hydropower equipment hierarchical model: firstly, manually constructing KKS coding data based on KKS coding rules, and mapping the KKS coding data with the logic equipment level obtained in the step 1 to form a complete instantiation hydropower equipment level model, wherein each node in the hydropower equipment level model has only unique KKS codes corresponding to the nodes;
For example: constructing an instantiated hierarchical model of the hydroelectric generating set; firstly, KKS coding data manually constructed based on KKS coding rules are mapped with the logic equipment level obtained in the step 1 to form a complete instantiation hydroelectric generating set level model, and in the hydroelectric generating set level model, only unique KKS codes are arranged on each node and correspond to each node, wherein the unique KKS codes are shown in a table 2.
Table 2 instantiates a hierarchical model of a hydro-generator set
Step 3, constructing a hydropower equipment code based on a KKS coding rule and an original old equipment code; acquiring an equipment coding data set A s={A1,…,An of original old equipment by using an information extraction mode, and manually constructing an equipment KKS coding data set KKS= { K 1,…,Kn } based on a KKS coding rule, wherein A n is an asset code of nth equipment, and K n is a KKS code of nth equipment; combining the device KKS code and the old device code to form a new double code C new={[ K1, A1],…[ Kn, An of the device, and forming a new double code data set of the device; mapping and matching the new double code C new with the existing old equipment code A s to realize one-to-one mapping of the old equipment tree and the new equipment tree;
for example: as shown in table 3. The KKS code and the new double code of the hydroelectric generating set are as follows:
Table 3 one-to-one mapping of old device tree to new device tree
Step 4, constructing a panoramic information model of various data of the hydroelectric equipment based on KKS codes and data association relations; the panoramic information comprises static information, dynamic information, knowledge and analysis methods of the hydroelectric equipment.
The static information comprises various information which is endowed by the equipment factory and is not changed along with the running state of the equipment, wherein the information comprises equipment factory information, inherent attributes and inherent parameters.
Defining an original coding data set of static information as T ( Static state )={T( Static state )1,…, T( Static state )n, wherein T ( Static state )n represents original coding of an nth piece of static information; static information data set K （ Static state ） of the device is constructed based on KKS coding and data association relation, and the expression is as follows:
K（ Static state ）={K（ Static state ）1,…,K（ Static state ）n}；
Wherein, K （ Static state ）n=[Kn+T( Static state )n ];
K （ Static state ）n represents: coding static information data of an nth device;
K n represents: KKS encoding of the nth device;
T ( Static state )n represents: original encoding of the nth static information;
the static information data code K （ Static state ）n of the nth device can be obtained through the combination of the T ( Static state )n and the K n, and the association between the device and the static information data can be realized rapidly;
the corresponding relation between the static information and the equipment is as follows: one device or component is mapped with a plurality of different pieces of static information, and one piece of static information can also be mapped with a plurality of similar devices or components.
The dynamic information contains real-time data generated in the running process of the equipment and result data generated by processing the real-time data, the data changes along with the running or state change of the equipment, and the data is measured by various monitoring equipment and sensors.
Defining an original coding data set of the dynamic information as T ( Dynamic state )={T( Dynamic state )1,…, T( Dynamic state )n, wherein T ( Dynamic state )n represents the original coding of the nth piece of dynamic information; dynamic information data set K （ Dynamic state ） of the device is constructed based on KKS coding and data association relation, and the expression is as follows:
K（ Dynamic state ）={K（ Dynamic state ）1,…,K（ Dynamic state ）n}；
wherein, K （ Dynamic state ）n=[Kn+T( Dynamic state )n ];
k （ Dynamic state ）n represents: coding dynamic information data of an nth device;
K n represents: KKS encoding of the nth device;
t ( Dynamic state )n represents: original coding of the nth dynamic information;
The dynamic information data code K （ Dynamic state ）n of the nth device can be obtained through the combination of the T ( Dynamic state )n and the K n, and the association between the device and the dynamic information data can be realized rapidly;
the correspondence between the dynamic information and the device is that one device or component is mapped with a plurality of dynamic information, but one dynamic information is mapped with only one device or component.
The knowledge comprises various knowledge precipitates related to the operation and maintenance of equipment or parts, including fault cases, mechanism models, overhaul and maintenance rules and various standards formed in the operation and maintenance of the equipment, and the knowledge also comprises multi-dimensional heterogeneous data such as structured data, unstructured data and the like;
defining an original encoding dataset of knowledge as T ( Knowledge of )={T( Knowledge of )1,…, T( Knowledge of )n, wherein T ( Knowledge of )n represents an original encoding of the nth knowledge; knowledge data set K （ Knowledge of ） of the device is constructed based on KKS coding and data association relation, and the expression is:
K（ Knowledge of ）={K（ Knowledge of ）1,…,K（ Knowledge of ）n}；
wherein, K （ Knowledge of ）n=[Kn+T( Knowledge of )n ];
k （ Knowledge of ）n represents: knowledge data encoding of the nth device;
K n represents: KKS encoding of the nth device;
T ( Knowledge of )n represents: original encoding of the nth knowledge;
Through the combination of the T ( Knowledge of )n and the K n, the knowledge data code K （ Knowledge of ）n of the nth device can be obtained, and the association between the device and the knowledge data can be realized rapidly;
the correspondence between the knowledge and the device is mapping between one device or component and a plurality of pieces of knowledge.
The analysis method comprises a traditional analysis method and algorithm, and also comprises various rules, indexes and algorithms such as various big data analysis methods and algorithms;
Defining an analysis method original coding data set as T ( Method of )={T( Method of )1,…, T( Method of )n, wherein T ( Method of )n represents original coding of an nth method; the expression of the data set K （ Method of ） of the method for constructing the equipment based on the KKS code and the data association relation is as follows:
K（ Method of ）={K（ Method of ）1,…,K（ Method of ）n}；
wherein, K （ Method of ）n=[Kn+T( Method of )n ];
k （ Method of ）n represents: data encoding of the method of the nth device;
K n represents: KKS encoding of the nth device;
T ( Method of )n represents: original encoding of the nth method;
By combining the T ( Method of )n with the K n, the data code K （ Method of ）n of the method of the nth device can be obtained, and the association of the device and the method can be realized quickly;
The corresponding relation between the instantiated analysis method K （ Method of ） and the equipment is one-to-one mapping.
And (3) extracting KKS codes in the panoramic information model of various data of the hydroelectric equipment constructed in the step (4), and carrying out one-to-one mapping with the instantiated hierarchical model of the hydroelectric equipment constructed in the step (2), and arranging the mapping results by taking the equipment as a center to form the panoramic information model by taking the equipment as the center.
For example: taking the construction of a dynamic information data set of the equipment as an example, panoramic information of the hydroelectric equipment is constructed. As shown in table 4, the original code T ( Dynamic state )n of the dynamic information is first carded to form a dataset T ( Dynamic state ) of the dynamic information. Each piece of data in the dataset has a specific device object corresponding to it. Dynamic information data K （ Dynamic state ）n of the device can thus be combined on the basis of the device object KKS code K n and the original code T ( Dynamic state )n of the dynamic information. These data are combined into the dynamic information dataset K （ Dynamic state ） for the device. Other information construction methods such as static information, knowledge and analysis methods of the device are the same as the construction of the dynamic information data set.
Table 4 device dynamic information dataset construction
The equipment panoramic information data set constructed based on the equipment KKS codes all comprises KKS codes of equipment objects, and when equipment panoramic information is constructed, the equipment panoramic data set taking hydropower equipment as the center can be formed rapidly by extracting KKS code fields of various information data sets applied by the equipment. The dataset is characterized by: (1) fast instantiation capability; (2) The knowledge and analysis method is associated with the equipment, so that the precipitation of the knowledge and the method is realized, and a new solution is provided for the precipitation of the equipment operation and maintenance experience.
The above embodiments are only preferred embodiments of the present invention, and should not be construed as limiting the present invention, and the scope of the present invention should be defined by the claims, including the equivalents of the technical features in the claims. I.e., equivalent replacement modifications within the scope of this invention are also within the scope of the invention.
Claims (2)
1. A hydropower equipment information model rapid construction method based on an industrial Internet platform is characterized by comprising the following steps:
Step 1, constructing a logic device hierarchical structure based on hydroelectric devices: the hydropower equipment is constructed into a multi-level set of general logic equipment hierarchical structures according to the containing relations of the system, the subsystem and the components, and the logic equipment hierarchical structures need to contain all types of similar equipment;
step 2, constructing an instantiated hydropower equipment hierarchical model: firstly, manually constructing KKS coding data based on KKS coding rules, and mapping the KKS coding data with the logic equipment level obtained in the step 1 to form a complete instantiation hydropower equipment level model, wherein each node in the hydropower equipment level model has only unique KKS codes corresponding to the nodes;
Step 3, constructing a hydropower equipment code based on a KKS coding rule and an original old equipment code; acquiring an equipment coding data set A s={A1,…,An of original old equipment by using an information extraction mode, and manually constructing an equipment KKS coding data set KKS= { K 1,…,Kn } based on a KKS coding rule, wherein A n is an asset code of nth equipment, and K n is a KKS code of nth equipment; combining the device KKS code and the old device code to form a new double code C new={[ K1, A1],…[ Kn, An of the device, and forming a new double code data set of the device; mapping and matching the new double code C new with the existing old equipment code A s to realize one-to-one mapping of the old equipment tree and the new equipment tree;
Step 4, constructing a panoramic information model of various data of the hydroelectric equipment based on KKS codes and data association relations; the panoramic information comprises static information, dynamic information, knowledge and analysis methods of the hydroelectric equipment;
In step 4, the static information comprises various types of information which are endowed by the equipment factory and cannot change along with the running state of the equipment, wherein the equipment factory information comprises equipment factory information, inherent properties and inherent parameters;
defining an original coding data set of static information as T ( Static state )={T( Static state )1,…, T( Static state )n, wherein T ( Static state )n represents original coding of an nth piece of static information; static information data set K （ Static state ） of the device is constructed based on KKS coding and data association relation, and the expression is as follows:
K（ Static state ）={K（ Static state ）1,…,K（ Static state ）n}；
Wherein, K （ Static state ）n=[Kn+T( Static state )n ];
K （ Static state ）n represents: coding static information data of an nth device;
K n represents: KKS encoding of the nth device;
T ( Static state )n represents: original encoding of the nth static information;
the static information data code K （ Static state ）n of the nth device can be obtained through the combination of the T ( Static state )n and the K n, and the association between the device and the static information data can be realized rapidly;
The corresponding relation between the static information and the equipment is as follows: one device or component maps with a plurality of different static information, and one static information can also map with a plurality of similar devices or components;
in step 4, the dynamic information contains real-time data generated in the running process of the equipment and result data generated by processing the real-time data, and the data changes along with the running or state change of the equipment and is measured by various monitoring equipment and sensors;
Defining an original coding data set of the dynamic information as T ( Dynamic state )={T( Dynamic state )1,…, T( Dynamic state )n, wherein T ( Dynamic state )n represents the original coding of the nth piece of dynamic information; dynamic information data set K （ Dynamic state ） of the device is constructed based on KKS coding and data association relation, and the expression is as follows:
K（ Dynamic state ）={K（ Dynamic state ）1,…,K（ Dynamic state ）n}；
wherein, K （ Dynamic state ）n=[Kn+T( Dynamic state )n ];
k （ Dynamic state ）n represents: coding dynamic information data of an nth device;
K n represents: KKS encoding of the nth device;
t ( Dynamic state )n represents: original coding of the nth dynamic information;
The dynamic information data code K （ Dynamic state ）n of the nth device can be obtained through the combination of the T ( Dynamic state )n and the K n, and the association between the device and the dynamic information data can be realized rapidly;
the corresponding relation between the dynamic information and the equipment is that one piece of equipment or part is mapped with a plurality of pieces of dynamic information, but one piece of dynamic information is only mapped with one piece of equipment or part;
In step 4, the knowledge comprises various knowledge precipitates related to the operation and maintenance of the equipment or the components, including fault cases, mechanism models, overhaul and maintenance rules and various standards formed in the operation and maintenance of the equipment, and the knowledge also comprises multidimensional heterogeneous data such as structured data, unstructured data and the like;
defining an original encoding dataset of knowledge as T ( Knowledge of )={T( Knowledge of )1,…, T( Knowledge of )n, wherein T ( Knowledge of )n represents an original encoding of the nth knowledge; knowledge data set K （ Knowledge of ） of the device is constructed based on KKS coding and data association relation, and the expression is:
K（ Knowledge of ）={K（ Knowledge of ）1,…,K（ Knowledge of ）n}；
wherein, K （ Knowledge of ）n=[Kn+T( Knowledge of )n ];
k （ Knowledge of ）n represents: knowledge data encoding of the nth device;
K n represents: KKS encoding of the nth device;
T ( Knowledge of )n represents: original encoding of the nth knowledge;
Through the combination of the T ( Knowledge of )n and the K n, the knowledge data code K （ Knowledge of ）n of the nth device can be obtained, and the association between the device and the knowledge data can be realized rapidly;
the corresponding relation between the knowledge and the equipment is mapping between one piece of equipment or a part and a plurality of pieces of knowledge;
In step 4, the analysis method comprises a traditional analysis method and algorithm, and also comprises various rules, indexes and algorithms such as various big data analysis methods and algorithms;
Defining an analysis method original coding data set as T ( Method of )={T( Method of )1,…, T( Method of )n, wherein T ( Method of )n represents original coding of an nth method; the expression of the data set K （ Method of ） of the method for constructing the equipment based on the KKS code and the data association relation is as follows:
K（ Method of ）={K（ Method of ）1,…,K（ Method of ）n}；
wherein, K （ Method of ）n=[Kn+T( Method of )n ];
k （ Method of ）n represents: data encoding of the method of the nth device;
K n represents: KKS encoding of the nth device;
T ( Method of )n represents: original encoding of the nth method;
By combining the T ( Method of )n with the K n, the data code K （ Method of ）n of the method of the nth device can be obtained, and the association of the device and the method can be realized quickly;
The corresponding relation between the instantiated analysis method K （ Method of ） and the equipment is one-to-one mapping.
2. The rapid construction method of the hydropower equipment information model based on the industrial internet platform according to claim 1, wherein the rapid construction method is characterized by comprising the following steps: and (3) extracting KKS codes in the panoramic information model of various data of the hydroelectric equipment constructed in the step (4), and carrying out one-to-one mapping with the instantiated hierarchical model of the hydroelectric equipment constructed in the step (2), and arranging the mapping results by taking the equipment as a center to form the panoramic information model by taking the equipment as the center.
Priority Applications (2)
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| CN116910130B (en) * | 2023-09-08 | 2023-12-26 | 中国长江电力股份有限公司 | Construction method of industrial data middle platform frame for hydropower equipment |
| CN116991903A (en) * | 2023-09-27 | 2023-11-03 | 中国长江电力股份有限公司 | A device-oriented industrial data classification and query method |
| CN118691207A (en) * | 2024-06-06 | 2024-09-24 | 国网青海省电力公司电力科学研究院 | Phase regulator management method, device, equipment and storage medium in power system |
| CN119323299A (en) * | 2024-09-03 | 2025-01-17 | 中国长江电力股份有限公司 | KKS-based intelligent display method for field work tasks of large hydropower station |
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