Micro-service-based thermal power generation equipment management method and corresponding device

Abstract

The invention relates to a thermal power generation equipment management method based on micro-service and a corresponding device. The method comprises the following steps: determining a space simulation model and a management business group of thermal power generation equipment; determining a micro-service block group of the thermal power generation equipment according to the management service group; on the basis of the logic relation between the management services, the execution result of each micro-service block and the logic response sequence, determining a Patrie network of the thermal power generation equipment, arranging a service response mechanism of each micro-service block through the Patrie network, and obtaining a full-life-cycle safety management process of the thermal power generation equipment; deploying the full-life-cycle security management process in a space simulation model through a cloud native method to obtain a micro-service space simulation model; and simulating and managing the micro-service space simulation model, and managing the thermal power generation equipment according to a simulation result. The thermal power generation equipment can be managed from multiple aspects, so that the production safety coefficient of the thermal power generation equipment can be improved, and the occurrence probability of safety accidents can be reduced.

Description

Technical Field

[0001] The present disclosure relates to the field of electronic technology, and in particular, to a microservice-based thermal power generation equipment management method and corresponding device. Background Art

[0002] Thermal power generation equipment is mainly used to convert fuel into electrical energy. Its power generation performance has the advantages of stability, high cost-effectiveness and high power generation efficiency. However, during the operation of thermal power generation equipment, there are often production safety hazards, which requires the management or maintenance of the operating thermal power generation equipment. In the related technology, the daily production operation of thermal power generation equipment is managed and the thermal power generation equipment after operation is maintained. Summary of the invention

[0003] The purpose of the present disclosure is to provide a microservice-based thermal power generation equipment management method and corresponding device to solve the technical problems existing in the related technology.

[0004] In order to achieve the above objectives, the present disclosure provides a microservice-based thermal power generation equipment management method, comprising: Determine the space simulation model and management business group of thermal power generation equipment; Determining a microservice block group of the thermal power generation equipment according to the management business group; Based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, the Petri network of the thermal power generation equipment is determined, and the service response mechanism of each microservice block in the microservice block group is arranged through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment; Deploy the full lifecycle security management process in the space simulation model through a cloud native method to obtain a microservice space simulation model; The microservice space simulation model is simulated and managed to obtain simulation results, and the thermal power generation equipment is managed according to the simulation results.

[0005] Optionally, a management business group of thermal power generation equipment is determined, including: Determining safety management requirements for the thermal power generation equipment; According to the safety management requirements, determining a plurality of functional modules that need to be managed for the thermal power generation equipment; Acquire a management service associated with each of the multiple function modules to obtain multiple management services; A plurality of the management services are determined as the management service group.

[0006] Optionally, determining the microservice block group of the thermal power generation equipment according to the management service group includes: For each management service in the management service group, determine the preset management process strategy, historical monitoring data and historical management data corresponding to the management service, and recursively split the historical monitoring data and the historical management data according to the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management service; Building the management deployment executor and application programming interface of the microservice block group through the fuzzy logic decision tree to obtain the microservice block; A plurality of microservice blocks are determined as the microservice block group.

[0007] Optionally, the determining of a preset management process strategy, historical monitoring data, and historical management data corresponding to the management service, and recursively splitting the historical monitoring data and the historical management data by the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management service includes: Constructing a fuzzy data management warehouse of the management business according to the historical monitoring data and the historical management data, and embedding the fuzzy data management warehouse into the target microservice of the microservice block group corresponding to the management business; A root node is constructed with the fuzzy data management warehouse as the starting point, and the root node is recursively split through the membership function to obtain internal branch nodes. When the purity value of the internal branch node does not reach the preset node purity value, the internal branch node is continued to be recursively split until the purity value of the new internal branch node reaches the preset node purity value to obtain the fuzzy logic decision tree, wherein the membership function is calculated through the preset management process strategy and the fuzzy data management warehouse.

[0008] Optionally, constructing the management deployment executor and application programming interface of the microservice block group through the fuzzy logic decision tree to obtain the microservice block includes: Matching the preset management process strategy of the management service with the fuzzy logic decision tree, defuzzifying the matched fuzzy logic decision tree to obtain leaf node values, and constructing the management deployment executor according to the leaf node values; Determine the application programming interface of the management deployment executor, and use a cloud native method to encapsulate the management deployment executor of the management business and the application programming interface in the microservices in the corresponding microservice block group into container images to obtain the microservice block.

[0009] Optionally, based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, the Petri network of the thermal power generation equipment is determined, and the service response mechanism of each microservice block in the microservice block group is arranged by the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment, including: The logical relationship is used as a directed edge, the execution result is used as a local node, the logical response order is used as a transition condition, and the historical safety management behavior of the thermal power generation equipment is topologically structured through the local nodes, the transition conditions and the directed edges to obtain the Petri network; Determine whether all the local nodes located in the front of the transition condition have marks according to the directed edge distribution of the Petri network, and when all the local nodes located in the front of the transition condition have marks, stimulate the transition condition to the local nodes located in the rear, and mark the transition condition as an activatable transition condition, otherwise, mark the transition condition as an unactivatable transition condition; Eliminating the non-stimulatable transition conditions in the Petri net, and updating the Petri net through the stimulatable transition conditions and the local nodes and the directed edge distribution after the stimulatable transition conditions are stimulated, so as to obtain a Petri net model; Through a cloud-native approach, container orchestration is performed on each microservice block in the microservice block group based on the Petri net model, and a service response mechanism of each microservice block in the microservice block group is set and introduced according to the Petri net model to obtain the full life cycle security management process.

[0010] Optionally, the method further comprises: Determining environmental parameters of the thermal power generation equipment; The simulation manages the microservice space simulation model to obtain a simulation result, and manages the thermal power generation equipment according to the simulation result, including: Performing simulation management on the microservice space simulation model based on the environmental parameters to obtain management activity simulation data of each microservice block; Constructing a polar coordinate diagram in the microservice space simulation model, and dividing a plurality of polar coordinate areas in the polar coordinate diagram according to the full lifecycle safety management process to obtain an initial polar coordinate diagram, wherein the polar coordinate areas are used to represent the management activity rule information of the microservice block; Fitting the management activity simulation data of each microservice block in the corresponding polar coordinate area of ​​the initial polar coordinate diagram one by one to obtain a multi-dimensional management activity simulation polar coordinate diagram; Calculate the degree of overlap between the multidimensional management activity simulation polar coordinate diagram and the multidimensional management activity standard polar coordinate diagram after registration to obtain an overall registration overlap degree, wherein the multidimensional management activity standard polar coordinate diagram is used to characterize the polar coordinate diagram of the microservice space simulation model under actual environmental parameter conditions; The thermal power generation equipment is managed according to the overall registration overlap.

[0011] Optionally, managing the thermal power generation equipment according to the overall registration overlap includes: When the overall registration overlap is greater than a preset registration overlap, managing the thermal power generation equipment according to the overall registration overlap; When the overall registration overlap is less than or equal to the preset registration overlap, the deployment exception data corresponding to the microservice space simulation model is updated, and the updated microservice space simulation model is simulated to obtain a simulation sub-result, and the thermal power generation equipment is managed through the simulation sub-result.

[0012] Optionally, updating the deployment exception data corresponding to the microservice space simulation model, simulating the updated microservice space simulation model to obtain a simulation sub-result, and managing the thermal power generation equipment through the simulation sub-result includes: Determine a sub-registration overlap of each polar coordinate region according to the overall registration overlap, and determine a target polar coordinate region where the sub-registration overlap is less than the preset registration overlap; Determine the management activity sub-simulation data and the management activity sub-standard data corresponding to the target polar coordinate area, and mark the difference data between the management activity sub-simulation data and the management activity sub-standard data as deployment abnormal data; Determine a management deployment topology map of the microservice space simulation model, extract a management deployment node layout corresponding to the deployment exception data according to the management deployment topology map, and calculate a gradient vector of the management deployment node layout; Using the gradient vector as a gradient climbing step value to update the deployment abnormality data, generating a target gradient climbing step value, and when the target gradient climbing step value is less than a preset gradient climbing step value, continuing to update the deployment abnormality data until the new target gradient climbing step value is greater than the preset gradient climbing step value, thereby obtaining deployment optimization data; The microservice space simulation model is updated by using the deployment optimization data, and the updated microservice space simulation model is simulated to obtain the simulation sub-result, and the thermal power generation equipment is managed by using the simulation sub-result.

[0013] Optionally, before managing the thermal power generation equipment according to the simulation result, the method further includes: Acquiring management activity data for managing the thermal power generation equipment; Performing standardized timestamp processing on the management activity data to obtain management activity sub-data, performing time series fitting on the management activity sub-data to obtain network nodes and network boundaries, and constructing an initial dynamic management network framework based on the network nodes and the network boundaries; Determine a network snapshot generated at a preset time step in the initial dynamic management network framework, wherein the preset time step is a time interval between two adjacent data points; Determine the fitting management activity data fitted at the preset time step, and calculate the degree center value of the network node and the edge weight value of the network boundary in the network snapshot according to the fitting management activity data, and determine the node characteristics and boundary characteristics of the network node in the network snapshot according to the degree center value and the edge weight value; Performing embedding analysis on the network snapshot according to the node features and the boundary features to obtain an initial node embedding representation; Taking the target time step as a reference, updating the initial node embedding representation corresponding to the time step before the target time step, until all time steps are updated, and obtaining the dynamic management network information; The dynamic management network information is transmitted to a terminal of management service of the thermal power generation equipment.

[0014] In a second aspect, the present disclosure provides a microservice-based full lifecycle management device, including: a first determination module, a second determination module, an orchestration module, a deployment module, and a simulation module; The first determination module is used to determine the spatial simulation model and management business group of the thermal power generation equipment; The second determination module is used to determine the microservice block group of the thermal power generation equipment according to the management business group; The orchestration module is used to determine the Petri network of the thermal power generation equipment based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, and to orchestrate the service response mechanism of each microservice block in the microservice block group through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment; The deployment module is used to deploy the full life cycle security management process in the space simulation model through a cloud native method to obtain a microservice space simulation model; The simulation module is used to simulate and manage the microservice space simulation model, obtain simulation results, and manage the thermal power generation equipment according to the simulation results.

[0015] Optionally, the first determining module includes: A third determination module is used to determine the safety management requirements of the thermal power generation equipment; A fourth determination module, used to determine a plurality of functional modules that need to be managed for the thermal power generation equipment according to the safety management requirements; A first data acquisition module is used to acquire management services associated with each of the multiple function modules to obtain multiple management services; The fifth determining module is used to determine a plurality of the management services as the management service group.

[0016] Optionally, the second determining module includes: A first analysis module is used to determine, for each management service in the management service group, a preset management process strategy, historical monitoring data, and historical management data corresponding to the management service, and recursively split the historical monitoring data and the historical management data according to the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management service; A first construction module is used to construct a management deployment executor and an application programming interface of the microservice block group through the fuzzy logic decision tree to obtain a microservice block; The sixth determining module is used to determine a plurality of microservice blocks as the microservice block group.

[0017] Optionally, the first analysis module includes: A second construction module is used to construct a fuzzy data management warehouse of the management business according to the historical monitoring data and the historical management data, and embed the fuzzy data management warehouse into the target microservice of the microservice block group corresponding to the management business; The second analysis module is used to construct a root node with the fuzzy data management warehouse as the starting point, and recursively split the root node through the membership function to obtain internal branch nodes. When the purity value of the internal branch node does not reach the preset node purity value, the internal branch node continues to be recursively split until the purity value of the new internal branch node reaches the preset node purity value to obtain the fuzzy logic decision tree, wherein the membership function is calculated by the preset management process strategy and the fuzzy data management warehouse.

[0018] Optionally, the first building block includes: A processing module, used for matching the preset management process strategy of the management service with the fuzzy logic decision tree, defuzzifying the matched fuzzy logic decision tree to obtain leaf node values, and constructing the management deployment executor according to the leaf node values; The encapsulation module is used to determine the application programming interface of the management deployment executor, and to encapsulate the management deployment executor of the management business and the application programming interface in the microservices in the corresponding microservice block group in a container image through a cloud native method to obtain the microservice block.

[0019] Optionally, the arrangement module includes: a structural topology module, used to use the logical relationship as a directed edge, the execution result as a local node, the logical response order as a transition condition, and to perform structural topology on the historical safety management behavior of the thermal power generation equipment through the local nodes, the transition conditions and the directed edges to obtain the Petri network; an excitation module, for judging whether all the local nodes located in front of the transition condition have marks according to the directed edge distribution of the Petri net, and when all the local nodes located in front of the transition condition have marks, the transition condition is excited to the local nodes located in the rear, and the transition condition is marked as an excitable transition condition, otherwise, the transition condition is marked as an unexcitable transition condition; A first updating module is used to remove the non-excitable transition conditions in the Petri network, and update the Petri network through the excitable transition conditions and the local nodes and the directed edge distribution after the excitable transition conditions are excited, so as to obtain a Petri network model; The orchestration submodule is used to perform container orchestration on each microservice block in the microservice block group based on the Petri net model through a cloud native method, and to set and introduce a service response mechanism of each microservice block in the microservice block group according to the Petri net model to obtain the full life cycle security management process.

[0020] Optionally, the device further comprises: A seventh determination module, used to determine the environmental parameters of the thermal power generation equipment; The simulation module comprises: A simulation management module, used to perform simulation management on the microservice space simulation model based on the environmental parameters to obtain management activity simulation data of each microservice block; A third construction module is used to construct a polar coordinate diagram in the microservice space simulation model, and divide a plurality of polar coordinate areas in the polar coordinate diagram according to the full life cycle safety management process to obtain an initial polar coordinate diagram, wherein the polar coordinate areas are used to represent the management activity rule information of the microservice block; A fitting module, used for fitting the management activity simulation data of each microservice block in the corresponding polar coordinate area of ​​the initial polar coordinate diagram one by one, to obtain a multi-dimensional management activity simulation polar coordinate diagram; A calculation module, used for calculating the overlap degree between the multidimensional management activity simulation polar coordinate diagram and the multidimensional management activity standard polar coordinate diagram after registration, and obtaining the overall registration overlap degree, wherein the multidimensional management activity standard polar coordinate diagram is used to characterize the polar coordinate diagram of the microservice space simulation model under the actual environmental parameter conditions; A management module is used to manage the thermal power generation equipment according to the overall registration overlap.

[0021] Optionally, the management module is used to: When the overall registration overlap is greater than a preset registration overlap, managing the thermal power generation equipment according to the overall registration overlap; When the overall registration overlap is less than or equal to the preset registration overlap, the deployment exception data corresponding to the microservice space simulation model is updated, and the updated microservice space simulation model is simulated to obtain a simulation sub-result, and the thermal power generation equipment is managed through the simulation sub-result.

[0022] Optionally, the management module includes: An eighth determination module, configured to determine a sub-registration overlap of each polar coordinate region according to the overall registration overlap, and determine a target polar coordinate region where the sub-registration overlap is less than the preset registration overlap; a marking module, used to determine the management activity sub-simulation data and the management activity sub-standard data corresponding to the target polar coordinate area, and mark the difference data between the management activity sub-simulation data and the management activity sub-standard data as deployment abnormal data; A data extraction module, used to determine the management deployment topology of the microservice space simulation model, extract the corresponding management deployment node layout in the deployment exception data according to the management deployment topology, and calculate the gradient vector of the management deployment node layout; a comparison module, configured to update the deployment abnormality data by taking the gradient vector as a gradient climbing step value, generate a target gradient climbing step value, and when the target gradient climbing step value is less than a preset gradient climbing step value, continue to update the deployment abnormality data until the new target gradient climbing step value is greater than the preset gradient climbing step value, thereby obtaining deployment optimization data; The second updating module is used to update the microservice space simulation model through the deployment optimization data, simulate the updated microservice space simulation model to obtain the simulation sub-result, and manage the thermal power generation equipment through the simulation sub-result.

[0023] Optionally, after managing the thermal power generation equipment according to the simulation result, the device further includes: A second data acquisition module is used to acquire management activity data for managing the thermal power generation equipment; A timing fitting module is used to perform standardized timestamp processing on the management activity data to obtain management activity sub-data, and perform timing fitting on the management activity sub-data to obtain network nodes and network boundaries, and construct an initial dynamic management network framework based on the network nodes and the network boundaries; A ninth determination module, configured to determine a network snapshot generated at a preset time step in the initial dynamic management network framework, wherein the preset time step is a time interval between two adjacent data points; a fourth determination module, configured to determine the fitting management activity data fitted at the preset time step, and calculate the degree center value of the network node and the edge weight value of the network boundary in the network snapshot according to the fitting management activity data, and determine the node characteristics and boundary characteristics of the network node in the network snapshot according to the degree center value and the edge weight value; An embedding analysis module, used to perform embedding analysis on the network snapshot according to the node features and the boundary features to obtain an initial node embedding representation; A third updating module is used to update the initial node embedding representation corresponding to the previous time step of the target time step based on the target time step, until all time steps are updated to obtain dynamic management network information; The data transmission module is used to transmit the dynamic management network information to the terminal of the management service of the thermal power generation equipment.

[0024] In a third aspect, the present disclosure provides a non-temporary computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the methods provided in the first aspect of the present disclosure.

[0025] In a fourth aspect, the present disclosure provides an electronic device, including: a memory having a computer program stored thereon; A processor is used to execute the computer program in the memory to implement the steps of any one of the methods provided in the first aspect of the present disclosure.

[0026] In a fifth aspect, the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any one of the methods provided in the first aspect of the present disclosure.

[0027] Through the above technical scheme, the microservice block group corresponding to the management business group of thermal power generation equipment is determined; based on the logical relationship between the management businesses in the management business group, the execution results of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, the Petri network of the thermal power generation equipment is determined, and the service response mechanism of each microservice block in the microservice block group is arranged through the Petri network to obtain the full life cycle safety management process; the full life cycle safety management process is deployed in the space simulation model of thermal power generation through the cloud native method to obtain the microservice space simulation model; the management microservice space simulation model is simulated to obtain the simulation results, and the thermal power generation equipment is managed according to the simulation results. According to the management business group and microservice block group of the thermal power generation equipment, the full life cycle safety management process is determined, and the full life cycle safety management process is deployed in the space simulation model, and the thermal power generation equipment is managed according to the simulation results of the space simulation model, so that the thermal power generation equipment can be managed from multiple angles, thereby improving the production safety factor of the thermal power generation equipment and reducing the probability of safety accidents.

[0028] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings: Figure 1 The figure is a schematic diagram showing a method for managing thermal power generation equipment based on microservices according to an exemplary embodiment of the present disclosure.

[0030] Figure 2 The figure is a schematic diagram showing a microservice-based thermal power generation equipment management device according to an exemplary embodiment of the present disclosure.

[0031] Figure 3 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0032] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0033] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the device is located and with the authorization given by the owner of the corresponding device.

[0034] In thermal power generation equipment, coal is mostly used as fuel, and the coal is burned in the combustion furnace. The heat generated by the coal combustion heats the water in the boiler to form high-pressure steam. With the development of science and technology, modern thermal power generation equipment mainly uses circulating fluidized bed combustion methods, natural circulation boilers and gas turbine power generation methods to improve combustion efficiency and reduce emissions. However, modern thermal power generation equipment has certain dangers during operation. For example, there is a fire risk during the storage, transportation and power generation of fuel. During operation, the boiler may be over-pressurized and over-heated due to improper pressure control, equipment failure or operating error, which may cause explosion accidents or equipment damage. Therefore, thermal power generation equipment needs to be managed.

[0035] In the related art, the daily production operation of thermal power generation equipment is usually managed, or the thermal power generation equipment after operation is maintained.

[0036] However, the inventors have found that when thermal power generation equipment is managed using the methods in the relevant technology, it is impossible to manage thermal power generation equipment in other states, which may cause safety hazards, reduce the operating safety factor of thermal power generation equipment, and increase the risk of safety accidents.

[0037] In view of this, the present disclosure provides a microservice-based thermal power generation equipment management method and corresponding device to solve the technical problems existing in the above-mentioned related technologies.

[0038] like Figure 1 As shown, Figure 1 is a schematic diagram showing a method for managing a thermal power generation equipment based on microservices according to an exemplary embodiment of the present disclosure, with reference to Figure 1 ,include: S101: Determine the space simulation model and management business group of thermal power generation equipment; S102: Determine a microservice block group of the thermal power generation equipment according to the management service group; S103: Based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, determine the Petri network of the thermal power generation equipment, and arrange the service response mechanism of each microservice block in the microservice block group through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment; S104: deploying the full lifecycle security management process in the space simulation model through a cloud native method to obtain a microservice space simulation model; S105: Simulate and manage the microservice space simulation model to obtain simulation results, and manage the thermal power generation equipment according to the simulation results.

[0039] Through the above technical scheme, the microservice block group corresponding to the management business group of thermal power generation equipment is determined; based on the logical relationship between the management businesses in the management business group, the execution results of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, the Petri network of the thermal power generation equipment is determined, and the service response mechanism of each microservice block in the microservice block group is arranged through the Petri network to obtain the full life cycle safety management process; the full life cycle safety management process is deployed in the space simulation model of thermal power generation through the cloud native method to obtain the microservice space simulation model; the management microservice space simulation model is simulated to obtain the simulation results, and the thermal power generation equipment is managed according to the simulation results. According to the management business group and microservice block group of the thermal power generation equipment, the full life cycle safety management process is determined, and the full life cycle safety management process is deployed in the space simulation model, and the thermal power generation equipment is managed according to the simulation results of the space simulation model, so that the thermal power generation equipment can be managed from multiple angles, thereby improving the production safety factor of the thermal power generation equipment and reducing the probability of safety accidents.

[0040] In order to enable those skilled in the art to better understand the microservice-based thermal power generation equipment management method provided by the present disclosure, the above steps are described in detail with examples below.

[0041] For example, the management service group may include at least two services of contractor and outsourced personnel management service, training and examination management service, maintenance management service, project management service, and task management service, etc., and the embodiments of the present disclosure do not specifically limit this.

[0042] The spatial simulation model can be a simulation model of thermal power generation equipment in the software. When constructing the spatial simulation model, the design drawings and spatial layout diagram of the thermal power generation equipment can be determined first, and then the design drawings and spatial layout diagram can be input into the PROE (Creo Parametric, 3D design software) model design software for construction to obtain the spatial simulation model.

[0043] Among possible approaches, identify the management business group of thermal power generation equipment, including: Determine the safety management requirements of the thermal power generation equipment; determine multiple functional modules that need to be managed for the thermal power generation equipment based on the safety management requirements; obtain management services associated with each of the multiple functional modules to obtain multiple management services; and determine the multiple management services as the management service group.

[0044] It should be understood that thermal power generation equipment usually burns fossil fuels to drive generators to generate electricity. In this process, a series of safety monitoring and management needs to be performed on the thermal power generation equipment, such as hidden danger management, risk management, technical supervision management, project management, energy-saving reliability management, and operation management. Therefore, it is necessary to determine the safety management requirements of thermal power generation equipment, and determine multiple functional modules based on the safety management requirements, wherein each functional module may include a monitoring module, an operation module, a management module, and a tool module, and the embodiments of the present disclosure do not make specific limitations on this. In each functional module, multiple management services are also included, and the multiple management services can be determined as a management service group. Among them, the management service may include at least one of a monitoring module, an operation module, a management module, and a tool module.

[0045] For example, after determining the management service group, the microservice block group of the corresponding thermal power generation equipment can be determined according to the management service group. The microservice block group can include multiple microservice blocks, and one management service in the management service group corresponds to one microservice block in the microservice block group.

[0046] In a possible manner, determining the microservice block group of the thermal power generation equipment according to the management service group includes: For each management service in the management service group, determine the preset management process strategy, historical monitoring data and historical management data corresponding to the management service, and recursively split the historical monitoring data and the historical management data according to the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management service; Building the management deployment executor and application programming interface of the microservice block group through the fuzzy logic decision tree to obtain the microservice block; A plurality of microservice blocks are determined as the microservice block group.

[0047] It should be understood that in each management business, the preset management process strategy, historical monitoring data and historical management data corresponding to the management business are included. Among them, the preset management process strategy can be a sequential process corresponding to the management business, and the historical monitoring data and historical management data can be extracted through the management log of the thermal power generation equipment. Thus, the management business group includes multiple preset management process measurements, multiple historical monitoring data and multiple historical management data. Afterwards, the historical monitoring data and the historical management data can be recursively split through the preset management process strategy to obtain the fuzzy logic decision tree corresponding to the management business. Among them, the recursive splitting process can be a processing process for decomposing a problem into smaller sub-problems to solve. The fuzzy logic decision tree can be a decision support tool that combines fuzzy logic with a decision tree.

[0048] In this embodiment, the management deployment executor and the application programming interface (API) of the microservice block group can be constructed through the fuzzy logic decision tree to obtain the microservice block. Each management business in the management business group is processed through the above steps to obtain multiple microservice blocks, and then the multiple microservice blocks can be determined as a microservice block group.

[0049] In a possible manner, the preset management process strategy, historical monitoring data and historical management data corresponding to the management business are determined, and the historical monitoring data and the historical management data are recursively split by the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management business, including: Constructing a fuzzy data management warehouse of the management business according to the historical monitoring data and the historical management data, and embedding the fuzzy data management warehouse into the target microservice of the microservice block group corresponding to the management business; A root node is constructed with the fuzzy data management warehouse as the starting point, and the root node is recursively split through the membership function to obtain internal branch nodes. When the purity value of the internal branch node does not reach the preset node purity value, the internal branch node is continued to be recursively split until the purity value of the new internal branch node reaches the preset node purity value to obtain the fuzzy logic decision tree, wherein the membership function is calculated through the preset management process strategy and the fuzzy data management warehouse.

[0050] It should be understood that the fuzzy data management warehouse can be a method for processing and analyzing through fuzzy logic in a data warehouse environment. In this embodiment, for each management business, a corresponding fuzzy data management warehouse can be constructed based on the historical monitoring data and historical management data of the management business, and then the fuzzy data management warehouse can be embedded in the microservice of the microservice block group corresponding to the management business. After that, a Gaussian membership function can be introduced, and the membership function between the preset management process strategy of each management business and the total fuzzy data management warehouse is calculated by the introduced Gaussian membership function. After that, a root node can be constructed with the fuzzy data management warehouse as the starting node, and the root node can be recursively split into internal branch nodes through the membership function to obtain multiple internal branch nodes, and the above steps are repeated to recursively split all internal branch nodes until the current node purity value reaches the preset node purity value, and the fuzzy logic decision tree of the management business is obtained.

[0051] By constructing a fuzzy logic decision tree through historical detection data, historical management data, and preset management process strategies, it can reflect the management logic of the preset management process strategy to generate historical monitoring data and historical management data, and is an overview of the rationality of running the entire management process. Therefore, the final output leaf node value can create a management deployment executor, thereby improving the accuracy of the independent management logic of each management business in the microservice framework, greatly reducing management errors, and achieving better expected management results compared to traditional management systems.

[0052] In a possible manner, the step of constructing the management deployment executor and the application programming interface of the microservice block group through the fuzzy logic decision tree to obtain the microservice block includes: Matching the preset management process strategy of the management service with the fuzzy logic decision tree, defuzzifying the matched fuzzy logic decision tree to obtain leaf node values, and constructing the management deployment executor according to the leaf node values; Determine the application programming interface of the management deployment executor, and use a cloud native method to encapsulate the management deployment executor of the management business and the application programming interface in the microservices in the corresponding microservice block group into container images to obtain the microservice block.

[0053] It should be understood that in this embodiment, when constructing the management deployment executor and application programming interface of the microservice block group based on the fuzzy logic decision tree, for each management business, the fuzzy logic decision tree can be matched and defuzzified based on the preset management process strategy corresponding to the management business, and all leaf node values ​​of the fuzzy logic decision tree can be output, and the management deployment executor can be constructed based on all leaf node values. After that, the application programming interface adapted to the management deployment executor can be obtained based on the big data network retrieval, and the management deployment executor and application programming interface of each management business can be containerized and encapsulated in the corresponding microservice using the cloud native method to obtain the microservice block of each management business.

[0054] Through the above technical solutions, the management system can be divided into multiple functional modules based on the cloud native method in terms of safety production management. Through these functional modules, multiple management businesses can be integrated and each management business can be separated into a microservice using the microservice framework to facilitate the separate development, deployment and update of each management business. This will reduce the coupling between different services, improve the flexibility and maintainability of the system, and form an efficient and integrated intelligent safety management system.

[0055] For example, after obtaining the microservice block group, the execution result of each microservice block in the microservice block group and the logical corresponding order of each microservice block can be determined. In the management business group, the logical relationship between each management business in the management business group can be determined, wherein the logical relationship can be the connection between two different management modules, such as project management can be combined with contractor and outsourced personnel management, thereby completing the responsibility management of outsourced contractors of thermal power generation equipment for daily execution of the project.

[0056] In this embodiment, a Petri net can be determined according to the logical relationship, the execution result and the logical corresponding order, wherein the Petri net can be used to describe and analyze the mathematical model of the discrete event system, and the Petri net is composed of the relationship description of the local points, the transition conditions and the directed edges. After that, the service response mechanism of each microservice block in the microservice block group can be arranged through the Petri net to obtain the full life cycle safety management process of the thermal power generation equipment. Among them, the full life cycle safety management process can be a series of management activities for identifying, evaluating, controlling and monitoring safety risks in the entire process from the design, development, testing, deployment to the final operation of the thermal power generation equipment.

[0057] In a possible manner, based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, the Petri network of the thermal power generation equipment is determined, and the service response mechanism of each microservice block in the microservice block group is arranged through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment, including: The logical relationship is used as a directed edge, the execution result is used as a local node, the logical response order is used as a transition condition, and the historical safety management behavior of the thermal power generation equipment is topologically structured through the local nodes, the transition conditions and the directed edges to obtain the Petri network; Determine whether all the local nodes located in the front of the transition condition have marks according to the directed edge distribution of the Petri network, and when all the local nodes located in the front of the transition condition have marks, stimulate the transition condition to the local nodes located in the rear, and mark the transition condition as an activatable transition condition, otherwise, mark the transition condition as an unactivatable transition condition; Eliminating the non-stimulatable transition conditions in the Petri net, and updating the Petri net through the stimulatable transition conditions and the local nodes and the directed edge distribution after the stimulatable transition conditions are stimulated, so as to obtain a Petri net model; Through a cloud-native approach, container orchestration is performed on each microservice block in the microservice block group based on the Petri net model, and a service response mechanism of each microservice block in the microservice block group is set and introduced according to the Petri net model to obtain the full life cycle security management process.

[0058] It should be understood that when generating a Petri net, the logical relationship can be used as a directed edge, the execution result can be used as a local node, and the logical response order can be used as a transition condition, wherein the directed edge can be used to characterize the logical relationship when managing the full life cycle safety management of thermal power generation equipment, and the local node can be used to characterize the management execution results of each microservice block in managing the deployment of the actuator within a preset time period. At the same time, based on the logical relationship, the next microservice block that needs to respond to the final management execution result after each microservice block generates different final management execution results can be discretely analyzed to obtain the logical response order of the microservice block.

[0059] After that, the historical safety management behavior of thermal power generation equipment can be topologically structured through local nodes, transition conditions, and directed edges to obtain the Petri network. Then, the distribution of directed edges in the Petri network can be used to determine whether all the local nodes located in the front of the transition condition are marked. If so, the transition condition is stimulated to the local node located in the back and marked as an activatable transition condition; if not, the transition condition is marked as an unactivatable transition condition. After that, all unactivatable transition conditions can be eliminated in the Petri network, and the Petri network can be updated based on the remaining activatable transition conditions and the corresponding local nodes and directed edge distribution after stimulation to generate an updated Petri network model.

[0060] Furthermore, cloud-native technology can be used to orchestrate containers for the microservice blocks of each management business based on the updated Petri net model, and a service response mechanism for each management business can be set and introduced according to the updated Petri net model to obtain the full life cycle safety management process of thermal power generation equipment.

[0061] Through the above technical solutions, the constructed Petri net can ensure that the production safety management of thermal power generation equipment can realize the full-domain and full-process management connection of the system according to the internal logical relationship between various management business links. Among them, in the Petri net, the directed edge from the local node to the transition condition represents the prerequisite for the transition, and the directed edge from the transition condition to the local node represents the result after the transition occurs. Then, by analyzing the Petri net, the more refined management logic level of each management business for other management businesses can be clarified. When all the preceding local nodes of a transition condition are marked, the transition condition can be stimulated. This stimulation mechanism simulates the occurrence of events or activities in the system and the change of system status. By stimulating the order of transitions and the distribution changes of marks, the possible operation sequence and different states of the system can be observed, ensuring that the Petri net accurately describes the process management logic behavior of the system, so that an efficient and accurate full-life cycle safety management process of thermal power generation equipment can be constructed based on the microservice framework, and the safety management reliability of the full-domain and full-process connection between various management businesses of the smart safety management system can be improved.

[0062] For example, the full lifecycle security management process can be automatically deployed in the space simulation model through the integration tools and continuous deployment tools in the cloud native method to obtain a microservice space simulation model. The cloud native method can be an application that supports building, deploying, and running in a cloud environment.

[0063] For example, after obtaining the microservice space simulation model, the microservice space simulation model can be simulated and managed to obtain simulation results, and the thermal power generation equipment can be managed according to the simulation results.

[0064] In a possible embodiment, the method further comprises: Determining environmental parameters of the thermal power generation equipment; The simulation manages the microservice space simulation model to obtain a simulation result, and manages the thermal power generation equipment according to the simulation result, including: Performing simulation management on the microservice space simulation model based on the environmental parameters to obtain management activity simulation data of each microservice block; Constructing a polar coordinate diagram in the microservice space simulation model, and dividing a plurality of polar coordinate areas in the polar coordinate diagram according to the full lifecycle safety management process to obtain an initial polar coordinate diagram, wherein the polar coordinate areas are used to represent the management activity rule information of the microservice block; Fitting the management activity simulation data of each microservice block in the corresponding polar coordinate area of ​​the initial polar coordinate diagram one by one to obtain a multi-dimensional management activity simulation polar coordinate diagram; Calculate the degree of overlap between the multidimensional management activity simulation polar coordinate diagram and the multidimensional management activity standard polar coordinate diagram after registration to obtain an overall registration overlap degree, wherein the multidimensional management activity standard polar coordinate diagram is used to characterize the polar coordinate diagram of the microservice space simulation model under actual environmental parameter conditions; The thermal power generation equipment is managed according to the overall registration overlap.

[0065] It should be understood that environmental parameters can be parameters such as temperature, humidity, pressure, fuel consumption, air volume, cooling water flow, steam flow, and water consumption in thermal power generation equipment. When simulating and managing the microservice space simulation model, simulation management can be performed in PROE (Pro / ENGINEER, computer-aided design) model design software. At the same time, the microservice space simulation model can be simulated and managed through the environmental parameters, and then the management activity simulation data corresponding to each microservice block can be obtained.

[0066] Polar coordinate charts can be used to represent data points in polar coordinates, and can also display the safety management periodicity of multi-dimensional management activity simulation data. In the polar coordinate chart, each polar coordinate area can represent the management activity specification of each microservice block for the full life cycle safety management process. For example, if a certain polar coordinate area represents the management activity specification of the project management business, then the corresponding multi-dimensional management activity simulation data is fitted in its polar coordinate area, which indicates the periodicity of the multi-dimensional management activity simulation data output based on the management activity specification of the project management business, and thus can show the accuracy of the deployment and operation of the full life cycle safety management process on thermal power generation equipment.

[0067] The multidimensional management activity simulation polar coordinate diagram and the multidimensional management activity standard polar coordinate diagram are registered, and the overall overlap degree of the multidimensional management activity simulation polar coordinate diagram and the multidimensional management activity standard polar coordinate diagram after registration is calculated in PROE model design software to obtain the overall registration overlap degree; then the thermal power generation equipment can be managed according to the overall registration overlap degree.

[0068] Through the above technical solution, the rationality and feasibility of the deployment and application of the full life cycle security management process built based on the microservice framework can be analyzed, which provides a reasonable and reliable analysis basis for the subsequent actual deployment of the full life cycle security management process based on the microservice framework, and greatly improves the management and operation stability of the smart security management system.

[0069] In a possible manner, the managing the thermal power generation equipment according to the overall registration overlap includes: When the overall registration overlap is greater than a preset registration overlap, managing the thermal power generation equipment according to the overall registration overlap; When the overall registration overlap is less than or equal to the preset registration overlap, the deployment exception data corresponding to the microservice space simulation model is updated, and the updated microservice space simulation model is simulated to obtain a simulation sub-result, and the thermal power generation equipment is managed through the simulation sub-result.

[0070] It should be understood that when managing thermal power generation equipment based on the overall registration overlap, the overall registration overlap can be compared with the preset registration overlap, and the thermal power generation equipment can be managed based on the comparison result, wherein the preset registration overlap can be used to characterize the threshold of whether the thermal power generation equipment can be directly managed.

[0071] For example, when the overall registration overlap is greater than the preset registration overlap, the thermal power generation equipment can be managed directly according to the overall registration overlap. Otherwise, it is necessary to update the deployment exception data corresponding to the microservice space simulation model, simulate the updated microservice space simulation model, and manage the thermal power generation equipment according to the obtained simulation sub-results, thereby improving the accuracy of managing the thermal power generation equipment.

[0072] In a possible manner, the deployment exception data corresponding to the microservice space simulation model is updated, and the updated microservice space simulation model is simulated to obtain a simulation sub-result, and the thermal power generation equipment is managed through the simulation sub-result, including: Determine a sub-registration overlap of each polar coordinate region according to the overall registration overlap, and determine a target polar coordinate region where the sub-registration overlap is less than the preset registration overlap; Determine the management activity sub-simulation data and the management activity sub-standard data corresponding to the target polar coordinate area, and mark the difference data between the management activity sub-simulation data and the management activity sub-standard data as deployment abnormal data; Determine a management deployment topology map of the microservice space simulation model, extract a management deployment node layout corresponding to the deployment exception data according to the management deployment topology map, and calculate a gradient vector of the management deployment node layout; Using the gradient vector as a gradient climbing step value to update the deployment abnormality data, generating a target gradient climbing step value, and when the target gradient climbing step value is less than a preset gradient climbing step value, continuing to update the deployment abnormality data until the new target gradient climbing step value is greater than the preset gradient climbing step value, thereby obtaining deployment optimization data; The microservice space simulation model is updated by using the deployment optimization data, and the updated microservice space simulation model is simulated to obtain the simulation sub-result, and the thermal power generation equipment is managed by using the simulation sub-result.

[0073] It should be understood that when the overall registration overlap is less than or equal to the preset registration overlap, it can represent that the automated deployment result at this time deviates from the standard management, and it is necessary to obtain the polar coordinate area in the multi-dimensional management activity simulation polar coordinate diagram that deviates from the standard management, that is, the target polar coordinate area. At the same time, the deployment anomaly data corresponding to the target polar coordinate area is obtained, and the management deployment node layout is optimized by global gradient climbing through the deployment anomaly data, so that the deployment anomaly data can be gradually tended to the management standard direction gradient optimization and the automated deployment results can be tuned and calibrated to the optimal state and mode, so that the management of thermal power generation equipment can be more accurate and stable, the management efficiency can be improved, and management omissions, errors and failures can be avoided. Among them, the gradient climbing update can avoid local optimality by adjusting the step size, and improve the optimization accuracy of the deployment anomaly data for the microservice space simulation model.

[0074] In a possible manner, when managing the thermal power generation equipment according to the simulation result, the method further includes: Acquiring management activity data for managing the thermal power generation equipment; Performing standardized timestamp processing on the management activity data to obtain management activity sub-data, performing time series fitting on the management activity sub-data to obtain network nodes and network boundaries, and constructing an initial dynamic management network framework based on the network nodes and the network boundaries; Determine a network snapshot generated at a preset time step in the initial dynamic management network framework, wherein the preset time step is a time interval between two adjacent data points; Determine the fitting management activity data fitted at the preset time step, and calculate the degree center value of the network node and the edge weight value of the network boundary in the network snapshot according to the fitting management activity data, and determine the node characteristics and boundary characteristics of the network node in the network snapshot according to the degree center value and the edge weight value; Performing embedding analysis on the network snapshot according to the node features and the boundary features to obtain an initial node embedding representation; Taking the target time step as a reference, updating the initial node embedding representation corresponding to the time step before the target time step, until all time steps are updated, and obtaining the dynamic management network information; The dynamic management network information is transmitted to a terminal of management service of the thermal power generation equipment.

[0075] It should be understood that the daily production operation, project progress, maintenance and inspection processes of thermal power generation equipment usually require the collaborative management of multiple departments. For example, the project management process may require the activity data of the thermal power generation equipment maintenance management process to obtain and update the fault maintenance progress of the thermal power generation project in real time and formulate a project plan. Therefore, the management activity data of each process of thermal power generation equipment often needs to be uploaded to the system in real time for synchronous sharing and connection, so as to improve the quality of safety collaborative management in the whole process of thermal power generation equipment production.

[0076] This embodiment collects the management data of each process of thermal power generation equipment into a data sharing network by constructing a dynamic embedded management network, and dynamically embeds and incrementally updates the management data by representing the node characteristics and boundary characteristics of the management data in the dynamic embedded network, thereby improving the highly centralized shared storage and collaborative call performance of the safety management activity data of the thermal power generation equipment, forming a data connection for the entire domain and process of the thermal power generation business, improving the efficiency of information synchronization and sharing, and ensuring the accuracy of real-time dynamic updates of data. Among them, each network snapshot represents the state of the network nodes and network boundaries at a specific time point, which can be used to extract the characteristics of the network nodes and network boundaries, and is the core step in constructing a dynamic embedded management network. For each time step, based on the embedded representation of the previous time step and combined with the current network snapshot, the node embedding is incrementally updated, which can enable real-time update and effectiveness of the management activity data, and improve the reliability of data analysis in the thermal power generation production management process.

[0077] In a possible way, the power generation task of the thermal power generation equipment can be obtained, and the thermal power generation equipment performs the power generation task and records the power generation condition data of the equipment at multiple preset time nodes to obtain multiple sets of power generation condition data of the equipment; the preset safety assessment tool of the thermal power generation equipment is extracted, and the preset safety assessment tool is used to perform safety assessment on multiple sets of power generation condition data to obtain a safety assessment score. If the safety assessment score is lower than the preset safety assessment score, several types of safety hazards that will occur after the safety assessment score of the thermal power generation equipment is reduced are obtained based on the big data network; Obtain the lowest critical multi-dimensional power generation parameters of each type of safety hazard generated by thermal power generation equipment, define them as production safety abnormal power generation parameters, and extract the response management decisions for production safety abnormal power generation parameters in the full life cycle management process; Classifying a plurality of management decisions into normal response management decisions and abnormal response management decisions according to the minimum critical multidimensional power generation parameters, and extracting a production power generation parameter set of the current power generation equipment based on multiple sets of equipment power generation condition data; If there are no abnormal production safety power generation parameters in the production power generation parameter set, the normal response management decision will be allocated to the full life cycle management process of the thermal power generation equipment to deal with the normal production safety management of the thermal power generation equipment in performing power generation tasks; if there are at least one or more abnormal production safety power generation parameters in the production power generation parameter set, the abnormal response management decision will be allocated to the full life cycle management system of the thermal power generation equipment to deal with abnormal production safety hazards of the thermal power generation equipment in performing power generation tasks, and then it can be identified whether there are power generation parameters with power generation safety hazards in the current production power generation parameters, and the corresponding response management decisions can be reasonably allocated according to the identification results, which can improve the adaptability and rationality of the full life cycle management system for normal and abnormal production safety management, avoid the occurrence rate of safety hazards of thermal power generation equipment, and improve the safety factor.

[0078] In a possible way, the power generation of thermal power generation equipment at multiple preset time nodes is obtained, and the power generation change rate is calculated based on the multiple power generation. If the power generation change rate is greater than the preset power generation change rate, the management activity data of the power generation change rate generated by the full life cycle management system is extracted and defined as abnormal management activity data; Obtain the maximum management characteristics of each management business microservice block in the full life cycle management process, and introduce the cosine similarity method to calculate the correlation between abnormal management activity data and the maximum management characteristics of each management business microservice block; Determine the management anomaly correlation of each management business microservice block that causes the abnormal management activity data according to the correlation, extract the management business microservice block corresponding to the management anomaly correlation greater than the preset management anomaly correlation, and mark it as a suspected management error microservice block; The actual management activity variables of each suspected management error microservice block within the preset time period are obtained, and the Bayesian inference algorithm is introduced to infer and estimate the actual management activity variables of each suspected management error microservice block within the preset time period to obtain the management anomaly probability of each suspected management error microservice block; if the management anomaly probability is greater than the preset management anomaly probability, the suspected management error microservice block is marked as a management error microservice block, and the management error microservice block is uploaded and recorded in the development update log of the full life cycle management system.

[0079] This embodiment can efficiently and accurately analyze the management anomaly correlation of each management business microservice in the full life cycle management process with the thermal power generation equipment according to the variation range of the production power generation of the thermal power generation equipment, thereby locating the management business microservice block that causes the abnormal power generation of the thermal power generation equipment in the full life cycle management system, and can continuously develop and update these microservice blocks with management anomalies, and optimize the management decision-making process, so as to improve the overall management performance of the full life cycle management system for the thermal power generation equipment, and can reduce the power generation deviation and fluctuation of the thermal power generation equipment.

[0080] Based on the same concept, this embodiment also discloses a full life cycle management device based on microservices, referring to Figure 2 , Figure 2 is a schematic diagram showing a microservice-based thermal power generation equipment management device 200 according to an exemplary embodiment of the present disclosure, such as Figure 2 As shown, it includes: a first determination module 201, a second determination module 202, an orchestration module 203, a deployment module 204 and a simulation module 205; The first determination module 201 is used to determine the spatial simulation model and management business group of the thermal power generation equipment; The second determination module 202 is used to determine the microservice block group of the thermal power generation equipment according to the management service group; The orchestration module 203 is used to determine the Petri network of the thermal power generation equipment based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, and to orchestrate the service response mechanism of each microservice block in the microservice block group through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment; The deployment module 204 is used to deploy the full lifecycle security management process in the space simulation model through a cloud native method to obtain a microservice space simulation model; The simulation module 205 is used to simulate and manage the microservice space simulation model, obtain simulation results, and manage the thermal power generation equipment according to the simulation results.

[0081] Optionally, the first determining module 201 includes: A third determination module is used to determine the safety management requirements of the thermal power generation equipment; A fourth determination module, used to determine a plurality of functional modules that need to be managed for the thermal power generation equipment according to the safety management requirements; A first data acquisition module is used to acquire management services associated with each of the multiple function modules to obtain multiple management services; The fifth determining module is used to determine a plurality of the management services as the management service group.

[0082] Optionally, the second determining module 202 includes: A first analysis module is used to determine, for each management service in the management service group, a preset management process strategy, historical monitoring data, and historical management data corresponding to the management service, and recursively split the historical monitoring data and the historical management data according to the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management service; A first construction module is used to construct a management deployment executor and an application programming interface of the microservice block group through the fuzzy logic decision tree to obtain a microservice block; The sixth determining module is used to determine a plurality of microservice blocks as the microservice block group.

[0083] Optionally, the first analysis module includes: A second construction module is used to construct a fuzzy data management warehouse of the management business according to the historical monitoring data and the historical management data, and embed the fuzzy data management warehouse into the target microservice of the microservice block group corresponding to the management business; The second analysis module is used to construct a root node with the fuzzy data management warehouse as the starting point, and recursively split the root node through the membership function to obtain internal branch nodes. When the purity value of the internal branch node does not reach the preset node purity value, the internal branch node continues to be recursively split until the purity value of the new internal branch node reaches the preset node purity value to obtain the fuzzy logic decision tree, wherein the membership function is calculated by the preset management process strategy and the fuzzy data management warehouse.

[0084] Optionally, the first building block includes: A processing module, used for matching the preset management process strategy of the management service with the fuzzy logic decision tree, defuzzifying the matched fuzzy logic decision tree to obtain leaf node values, and constructing the management deployment executor according to the leaf node values; The encapsulation module is used to determine the application programming interface of the management deployment executor, and to encapsulate the management deployment executor of the management business and the application programming interface in the microservices in the corresponding microservice block group in a container image through a cloud native method to obtain the microservice block.

[0085] Optionally, the arrangement module 203 includes: a structural topology module, used to use the logical relationship as a directed edge, the execution result as a local node, the logical response order as a transition condition, and to perform structural topology on the historical safety management behavior of the thermal power generation equipment through the local nodes, the transition conditions and the directed edges to obtain the Petri network; an excitation module, for judging whether all the local nodes located in front of the transition condition have marks according to the directed edge distribution of the Petri net, and when all the local nodes located in front of the transition condition have marks, the transition condition is excited to the local nodes located in the rear, and the transition condition is marked as an excitable transition condition, otherwise, the transition condition is marked as an unexcitable transition condition; A first updating module is used to remove the non-excitable transition conditions in the Petri network, and update the Petri network through the excitable transition conditions and the local nodes and the directed edge distribution after the excitable transition conditions are excited, so as to obtain a Petri network model; The orchestration submodule is used to perform container orchestration on each microservice block in the microservice block group based on the Petri net model through a cloud native method, and to set and introduce a service response mechanism of each microservice block in the microservice block group according to the Petri net model to obtain the full life cycle security management process.

[0086] Optionally, the device 200 further comprises: A seventh determination module, used to determine the environmental parameters of the thermal power generation equipment; The simulation module comprises: A simulation management module, used to perform simulation management on the microservice space simulation model based on the environmental parameters to obtain management activity simulation data of each microservice block; A third construction module is used to construct a polar coordinate diagram in the microservice space simulation model, and divide a plurality of polar coordinate areas in the polar coordinate diagram according to the full life cycle safety management process to obtain an initial polar coordinate diagram, wherein the polar coordinate areas are used to represent the management activity rule information of the microservice block; A fitting module, used for fitting the management activity simulation data of each microservice block in the corresponding polar coordinate area of ​​the initial polar coordinate diagram one by one, to obtain a multi-dimensional management activity simulation polar coordinate diagram; A calculation module, used for calculating the overlap degree between the multidimensional management activity simulation polar coordinate diagram and the multidimensional management activity standard polar coordinate diagram after registration, and obtaining the overall registration overlap degree, wherein the multidimensional management activity standard polar coordinate diagram is used to characterize the polar coordinate diagram of the microservice space simulation model under the actual environmental parameter conditions; A management module is used to manage the thermal power generation equipment according to the overall registration overlap.

[0087] Optionally, the management module is used to: When the overall registration overlap is greater than a preset registration overlap, managing the thermal power generation equipment according to the overall registration overlap; When the overall registration overlap is less than or equal to the preset registration overlap, the deployment exception data corresponding to the microservice space simulation model is updated, and the updated microservice space simulation model is simulated to obtain a simulation sub-result, and the thermal power generation equipment is managed through the simulation sub-result.

[0088] Optionally, the management module includes: An eighth determination module, configured to determine a sub-registration overlap of each polar coordinate region according to the overall registration overlap, and determine a target polar coordinate region where the sub-registration overlap is less than the preset registration overlap; a marking module, used to determine the management activity sub-simulation data and the management activity sub-standard data corresponding to the target polar coordinate area, and mark the difference data between the management activity sub-simulation data and the management activity sub-standard data as deployment abnormal data; A data extraction module, used to determine the management deployment topology of the microservice space simulation model, extract the corresponding management deployment node layout in the deployment exception data according to the management deployment topology, and calculate the gradient vector of the management deployment node layout; a comparison module, configured to update the deployment abnormality data by taking the gradient vector as a gradient climbing step value, generate a target gradient climbing step value, and when the target gradient climbing step value is less than a preset gradient climbing step value, continue to update the deployment abnormality data until the new target gradient climbing step value is greater than the preset gradient climbing step value, thereby obtaining deployment optimization data; The second updating module is used to update the microservice space simulation model through the deployment optimization data, simulate the updated microservice space simulation model to obtain the simulation sub-result, and manage the thermal power generation equipment through the simulation sub-result.

[0089] Optionally, after managing the thermal power generation equipment according to the simulation result, the device further includes: A second data acquisition module is used to acquire management activity data for managing the thermal power generation equipment; A timing fitting module is used to perform standardized timestamp processing on the management activity data to obtain management activity sub-data, and perform timing fitting on the management activity sub-data to obtain network nodes and network boundaries, and construct an initial dynamic management network framework based on the network nodes and the network boundaries; A ninth determination module, configured to determine a network snapshot generated at a preset time step in the initial dynamic management network framework, wherein the preset time step is a time interval between two adjacent data points; a fourth determination module, configured to determine the fitting management activity data fitted at the preset time step, and calculate the degree center value of the network node and the edge weight value of the network boundary in the network snapshot according to the fitting management activity data, and determine the node characteristics and boundary characteristics of the network node in the network snapshot according to the degree center value and the edge weight value; An embedding analysis module, used to perform embedding analysis on the network snapshot according to the node features and the boundary features to obtain an initial node embedding representation; A third updating module is used to update the initial node embedding representation corresponding to the previous time step of the target time step based on the target time step, until all time steps are updated to obtain dynamic management network information; The data transmission module is used to transmit the dynamic management network information to the terminal of the management service of the thermal power generation equipment.

[0090] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0091] Based on the same concept, this embodiment also discloses a non-temporary computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the microservice-based full lifecycle management method disclosed in this embodiment are implemented.

[0092] Based on the same concept, this embodiment also discloses an electronic device, including: a memory having a computer program stored thereon; A processor is used to execute the computer program in the memory to implement the steps of the microservice-based full lifecycle management method disclosed in this embodiment.

[0093] Figure 3 FIG. 1 is a block diagram of an electronic device 300 according to an exemplary embodiment. Figure 3 As shown, the electronic device 300 may include: a processor 301 , a memory 302 . The electronic device 300 may also include one or more of a multimedia component 303 , an input / output (I / O) interface 304 , and a communication component 305 .

[0094] The processor 301 is used to control the overall operation of the electronic device 300 to complete all or part of the steps in the above-mentioned microservice-based full life cycle management method. The memory 302 is used to store various types of data to support the operation of the electronic device 300, which may include, for example, instructions for any application or method used to operate on the electronic device 300, and application-related data, such as contact data, messages sent and received, pictures, audio, video, etc. The memory 302 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 303 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 302 or sent through the communication component 305. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 304 provides an interface between the processor 301 and other interface modules, and the other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 305 is used for wired or wireless communication between the electronic device 300 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 305 may include: Wi-Fi module, Bluetooth module, NFC module, etc.

[0095] In an exemplary embodiment, the electronic device 300 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned microservice-based full life cycle management method.

[0096] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned microservice-based full lifecycle management method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 302 including program instructions, and the above-mentioned program instructions can be executed by the processor 301 of the electronic device 300 to complete the above-mentioned microservice-based full lifecycle management method.

[0097] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0098] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0099] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A microservice-based thermal power generation equipment management method, characterized in that: include: Determine the space simulation model and management business group of thermal power generation equipment; Determining a microservice block group of the thermal power generation equipment according to the management business group; Based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, the Petri network of the thermal power generation equipment is determined, and the service response mechanism of each microservice block in the microservice block group is arranged through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment; Deploy the full lifecycle security management process in the space simulation model through a cloud native method to obtain a microservice space simulation model; The microservice space simulation model is simulated and managed to obtain simulation results, and the thermal power generation equipment is managed according to the simulation results.

2. The microservice-based thermal power generation equipment management method according to claim 1, characterized in that: Determine the management business group of thermal power generation equipment, including: Determining safety management requirements for the thermal power generation equipment; According to the safety management requirements, determining a plurality of functional modules that need to be managed for the thermal power generation equipment; Acquire a management service associated with each of the multiple function modules to obtain multiple management services; A plurality of the management services are determined as the management service group.

3. The microservice-based thermal power generation equipment management method according to claim 1, characterized in that: Determining the microservice block group of the thermal power generation equipment according to the management business group includes: For each management service in the management service group, determine the preset management process strategy, historical monitoring data and historical management data corresponding to the management service, and recursively split the historical monitoring data and the historical management data according to the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management service; Building the management deployment executor and application programming interface of the microservice block group through the fuzzy logic decision tree to obtain the microservice block; A plurality of microservice blocks are determined as the microservice block group.

4. The microservice-based thermal power generation equipment management method according to claim 3 is characterized in that: The determining of the preset management process strategy, historical monitoring data and historical management data corresponding to the management business, and recursively splitting the historical monitoring data and the historical management data by the preset management process strategy to obtain a fuzzy logic decision tree corresponding to the management business, includes: Constructing a fuzzy data management warehouse of the management business according to the historical monitoring data and the historical management data, and embedding the fuzzy data management warehouse into the target microservice of the microservice block group corresponding to the management business; A root node is constructed with the fuzzy data management warehouse as the starting point, and the root node is recursively split through the membership function to obtain internal branch nodes. When the purity value of the internal branch node does not reach the preset node purity value, the internal branch node is continued to be recursively split until the purity value of the new internal branch node reaches the preset node purity value to obtain the fuzzy logic decision tree, wherein the membership function is calculated through the preset management process strategy and the fuzzy data management warehouse.

5. The microservice-based thermal power generation equipment management method according to claim 3 is characterized in that: The method of constructing the management deployment executor and the application programming interface of the microservice block group through the fuzzy logic decision tree to obtain the microservice block includes: Matching the preset management process strategy of the management service with the fuzzy logic decision tree, defuzzifying the matched fuzzy logic decision tree to obtain leaf node values, and constructing the management deployment executor according to the leaf node values; Determine the application programming interface of the management deployment executor, and use a cloud native method to encapsulate the management deployment executor of the management business and the application programming interface in the microservices in the corresponding microservice block group into container images to obtain the microservice block.

6. The microservice-based thermal power generation equipment management method according to claim 1, characterized in that: The method comprises: determining the Petri network of the thermal power generation equipment based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, and arranging the service response mechanism of each microservice block in the microservice block group through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment, including: The logical relationship is used as a directed edge, the execution result is used as a local node, the logical response order is used as a transition condition, and the historical safety management behavior of the thermal power generation equipment is topologically structured through the local nodes, the transition conditions and the directed edges to obtain the Petri network; Determine whether all the local nodes located in the front of the transition condition have marks according to the directed edge distribution of the Petri network, and when all the local nodes located in the front of the transition condition have marks, stimulate the transition condition to the local nodes located in the rear, and mark the transition condition as an activatable transition condition, otherwise, mark the transition condition as an unactivatable transition condition; Eliminating the non-stimulatable transition conditions in the Petri net, and updating the Petri net through the stimulatable transition conditions and the local nodes and the directed edge distribution after the stimulatable transition conditions are stimulated, so as to obtain a Petri net model; Through a cloud-native approach, container orchestration is performed on each microservice block in the microservice block group based on the Petri net model, and a service response mechanism of each microservice block in the microservice block group is set and introduced according to the Petri net model to obtain the full life cycle security management process.

7. The microservice-based thermal power generation equipment management method according to claim 1, characterized in that: The method further comprises: Determining environmental parameters of the thermal power generation equipment; The simulation manages the microservice space simulation model to obtain a simulation result, and manages the thermal power generation equipment according to the simulation result, including: Performing simulation management on the microservice space simulation model based on the environmental parameters to obtain management activity simulation data of each microservice block; Constructing a polar coordinate diagram in the microservice space simulation model, and dividing a plurality of polar coordinate areas in the polar coordinate diagram according to the full lifecycle safety management process to obtain an initial polar coordinate diagram, wherein the polar coordinate areas are used to represent the management activity rule information of the microservice block; Fitting the management activity simulation data of each microservice block in the corresponding polar coordinate area of ​​the initial polar coordinate diagram one by one to obtain a multi-dimensional management activity simulation polar coordinate diagram; Calculating the degree of overlap between the multidimensional management activity simulation polar coordinate diagram and the multidimensional management activity standard polar coordinate diagram after registration to obtain an overall registration overlap degree, wherein the multidimensional management activity standard polar coordinate diagram is used to characterize the polar coordinate diagram of the microservice space simulation model under actual environmental parameter conditions; The thermal power generation equipment is managed according to the overall registration overlap.

8. The microservice-based thermal power generation equipment management method according to claim 7, characterized in that: The managing the thermal power generation equipment according to the overall registration overlap comprises: When the overall registration overlap is greater than a preset registration overlap, managing the thermal power generation equipment according to the overall registration overlap; When the overall registration overlap is less than or equal to the preset registration overlap, the deployment exception data corresponding to the microservice space simulation model is updated, and the updated microservice space simulation model is simulated to obtain a simulation sub-result, and the thermal power generation equipment is managed through the simulation sub-result.

9. The microservice-based thermal power generation equipment management method according to claim 8, characterized in that: The updating of the deployment exception data corresponding to the microservice space simulation model, simulating the updated microservice space simulation model to obtain a simulation sub-result, and managing the thermal power generation equipment through the simulation sub-result includes: Determine a sub-registration overlap of each polar coordinate region according to the overall registration overlap, and determine a target polar coordinate region where the sub-registration overlap is less than the preset registration overlap; Determine the management activity sub-simulation data and the management activity sub-standard data corresponding to the target polar coordinate area, and mark the difference data between the management activity sub-simulation data and the management activity sub-standard data as deployment abnormal data; Determine a management deployment topology map of the microservice space simulation model, extract a management deployment node layout corresponding to the deployment exception data according to the management deployment topology map, and calculate a gradient vector of the management deployment node layout; Using the gradient vector as a gradient climbing step value to update the deployment abnormality data, generating a target gradient climbing step value, and when the target gradient climbing step value is less than a preset gradient climbing step value, continuing to update the deployment abnormality data until the new target gradient climbing step value is greater than the preset gradient climbing step value, thereby obtaining deployment optimization data; The microservice space simulation model is updated by using the deployment optimization data, and the updated microservice space simulation model is simulated to obtain the simulation sub-result, and the thermal power generation equipment is managed by using the simulation sub-result.

10. The microservice-based thermal power generation equipment management method according to any one of claims 1 to 9, characterized in that: When managing the thermal power generation equipment according to the simulation results, the method further includes: Acquiring management activity data for managing the thermal power generation equipment; Performing standardized timestamp processing on the management activity data to obtain management activity sub-data, performing time series fitting on the management activity sub-data to obtain network nodes and network boundaries, and constructing an initial dynamic management network framework based on the network nodes and the network boundaries; Determine a network snapshot generated at a preset time step in the initial dynamic management network framework, wherein the preset time step is a time interval between two adjacent data points; Determine the fitting management activity data fitted at the preset time step, and calculate the degree center value of the network node and the edge weight value of the network boundary in the network snapshot according to the fitting management activity data, and determine the node characteristics and boundary characteristics of the network node in the network snapshot according to the degree center value and the edge weight value; Performing embedding analysis on the network snapshot according to the node features and the boundary features to obtain an initial node embedding representation; Taking the target time step as a reference, updating the initial node embedding representation corresponding to the time step before the target time step, until all time steps are updated, and obtaining the dynamic management network information; The dynamic management network information is transmitted to a terminal of management service of the thermal power generation equipment.

11. A microservice-based thermal power generation equipment management device, characterized in that: include: A first determination module, a second determination module, an orchestration module, a deployment module, and a simulation module; The first determination module is used to determine the spatial simulation model and management business group of the thermal power generation equipment; The second determination module is used to determine the microservice block group of the thermal power generation equipment according to the management business group; The orchestration module is used to determine the Petri network of the thermal power generation equipment based on the logical relationship between the management services in the management service group, the execution result of each microservice block in the microservice block group, and the logical response order of each microservice block in the microservice block group, and to orchestrate the service response mechanism of each microservice block in the microservice block group through the Petri network to obtain the full life cycle safety management process of the thermal power generation equipment; The deployment module is used to deploy the full life cycle security management process in the space simulation model through a cloud native method to obtain a microservice space simulation model; The simulation module is used to simulate and manage the microservice space simulation model, obtain simulation results, and manage the thermal power generation equipment according to the simulation results.

12. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

13. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 10.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

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