Thermal control maintenance management system of thermal power plant
By analyzing needs, collecting data, building prediction models, and using AR and VR technology for status identification and maintenance judgment in thermal power plant thermal control systems, the problem of fault diagnosis and prediction relying on manual experience in the existing technology has been solved, and efficient Fault diagnosis and energy efficiency management ensure power generation efficiency and safety.
Patent Information
- Application Number
- CN202411495366.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-24
- Publication Date
- 2025-01-21
AI Technical Summary
The existing thermal power plant thermal control systems rely on manual experience and rules in fault diagnosis and prediction, lack accurate data analysis and model prediction, have relatively extensive energy efficiency management, and lack data analysis and optimization measures for specific equipment and operating status.
By analyzing the thermal control system requirements of thermal power plants, we determine data collection points, collect and analyze equipment data, build prediction models, use AR and VR technology for status identification and maintenance judgment, and ultimately optimize energy management.
The level of intelligence of the thermal control system has been improved, the diagnosis and prediction of accurate faults are achieved, and the level of energy efficiency management is improved, thereby ensuring the efficiency and safety of power generation.
Smart Images
Figure CN119338442A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of intelligent maintenance technology, and in particular to a thermal control maintenance management system for a thermal power plant. Background Art
[0002] As a key link in the thermal power generation process, the thermal control system of a thermal power plant is crucial to ensuring power generation efficiency and safety. At present, the thermal control system is developing towards automation and intelligence, mainly using traditional automatic control technology, combined with SCADA (supervisory control and data acquisition) system and some fault diagnosis systems. These technologies have achieved monitoring and control of thermal control equipment to a certain extent, but there are still limitations. Fault diagnosis and prediction mainly rely on manual experience and rules, lack of accurate data analysis and model prediction, energy efficiency management is relatively extensive, and lack of data analysis and optimization measures for specific equipment and operating status.
[0003] Therefore, the present invention provides a thermal control maintenance management system for a thermal power plant. Summary of the invention
[0004] The present invention provides a thermal control maintenance management system for a thermal power plant. The system analyzes the needs of the thermal control system of the thermal power plant, determines data collection points, collects and analyzes equipment data, builds a prediction model, uses AR and VR technologies to perform status identification and maintenance judgment, and finally optimizes energy management. It improves the intelligence level of the thermal control system, realizes accurate fault diagnosis and prediction, and improves the energy efficiency management level, thereby ensuring power generation efficiency and safety.
[0005] The present invention provides a thermal control maintenance management system for a thermal power plant, comprising: Data acquisition module: Analyze the actual needs of the thermal control system of the thermal power plant, determine the data collection points of the thermal control equipment of the thermal control system of the thermal power plant based on the actual needs, and obtain historical thermal control equipment data based on the data collection points; Model building module: Analyze historical thermal control equipment data to obtain fault-related features and energy efficiency-related features, filter and mark historical thermal control equipment data according to the fault-related features and energy efficiency-related features, obtain fault-related data and energy efficiency-related data, and build a prediction model based on data collection points and marking results; Maintenance module: Develop corresponding AR applications based on the prediction model, identify the current status of the thermal control equipment based on the AR application, create VR scenes based on the prediction model, make maintenance judgments on the current status of the thermal control equipment based on the VR scenes, and maintain the thermal control equipment; Optimization module: Optimize energy management of thermal control equipment based on maintenance results.
[0006] The present invention provides a thermal control maintenance management system for a thermal power plant, a data acquisition module, comprising: Actual demand unit: conduct functional evaluation of thermal control systems of thermal power plants, obtain the functional evaluation results, understand the relevant technologies of thermal control systems of thermal power plants, and determine the actual needs of thermal control systems of thermal power plants by combining the functional evaluation results with relevant technologies; A collection point determination unit is configured to determine the type of data that needs to be collected according to the actual needs of the thermal control system of the thermal power plant, and to perform a first thermal control device classification on the thermal control equipment of the thermal control system of the thermal power plant using the function evaluation result. At the same time, the thermal control equipment is classified into a second thermal control device classification using the data type, and the data collection point of the thermal control equipment is determined based on the first thermal control device classification, and historical thermal control equipment data is collected at the data collection point according to the second thermal control device classification.
[0007] The present invention provides a thermal control maintenance management system for a thermal power plant, a model building module, comprising: Feature extraction unit: According to the working principle and actual needs of each thermal control device, the fault feature analysis and energy efficiency feature analysis of the historical thermal control device data are performed respectively, and the fault-related features and energy efficiency-related features are listed; Data extraction unit: obtains the operation requirements of the thermal control equipment to derive the fault-related characteristics and the energy efficiency-related characteristics, obtains the fault-derived characteristics and the energy efficiency-derived characteristics, performs a first screening on the historical thermal control equipment data according to the fault correlation between the historical thermal control equipment data and the fault-derived characteristics, and first marks the first screening results to obtain the fault-related data, and at the same time, performs a second screening on the historical thermal control equipment data according to the energy efficiency correlation between the historical thermal control equipment data and the energy efficiency-derived characteristics, and second marks the second screening results to obtain the energy efficiency-related data; Prediction model unit: a third mark is performed on the data collection point based on the fault-related data and the energy efficiency-related data, and a prediction model is constructed according to the first mark, the second mark and the third mark.
[0008] The present invention provides a thermal control maintenance management system for a thermal power plant, a maintenance module, comprising: Acquire functional units: set the overall goal of the thermal control system of the thermal power plant according to the actual needs of the thermal control system of the thermal power plant, list the first basic functions of the AR application based on the overall goal, refine the first basic functions according to the detailed function table, and obtain the first function to be realized; AR unit: obtaining the actual operating environment of the thermal control equipment of the thermal power plant and the use of the thermal control equipment in the actual operating environment, determining the worker demand based on the actual operating environment and the use of the thermal control equipment, arranging the scene for the AR application according to the prediction result output by the prediction model combined with the worker demand and the first function to be realized, forming an AR application, and outputting the current state of the thermal control equipment of the thermal control equipment based on the AR application; VR unit: based on the overall goal, lists the second basic functions of the VR application, extracts maintenance-related data from the historical thermal control device data according to the current state of the thermal control device, and combines the second basic functions with the maintenance-related data to form a VR scene; Judgment unit: Make maintenance judgments on the corresponding thermal control equipment based on the VR scene, and perform maintenance simulation on the thermal control equipment in the VR scene. Make validity judgments on the maintenance simulation results based on maintenance-related data, and perform actual operations on the maintenance simulation results that are higher than the preset effective values to maintain the thermal control equipment.
[0009] The present invention provides a thermal control maintenance management system for a thermal power plant, an AR unit, comprising: Worker demand block: Analyze the actual operating environment of thermal control equipment in thermal power plants, evaluate the impact of the actual operating environment on worker operations, and derive environmental impact requirements. At the same time, collect the use of thermal control equipment for each thermal control equipment in the actual operating environment, analyze the use of thermal control equipment, determine the potential maintenance requirements of the corresponding thermal control equipment, and combine the environmental impact requirements and potential maintenance requirements to derive worker requirements. Current status block: further refine the worker needs according to the output results of the prediction model, clarify the safety requirements of the workers in different actual operating environments based on the refined worker needs, arrange the AR application scene in combination with the refined worker needs, safety requirements and the first function to be implemented, and output the current status of the thermal control equipment based on the AR application.
[0010] The present invention provides a thermal control maintenance management system for a thermal power plant, a judgment unit, comprising: Judgment block: obtain the real-time status data of the thermal control equipment in the VR scene, compare the maintenance-related data with the real-time status data, and determine whether the corresponding thermal control equipment needs maintenance based on the comparison results; Simulation block: If maintenance is required, the corresponding maintenance simulation operation is obtained according to the maintenance-related data, the maintenance simulation operation is performed on the corresponding thermal control equipment in the VR scene, the simulation data during the maintenance simulation operation is collected, and the effective value of the maintenance simulation result is calculated according to the simulation data: , where V represents the validity function of the maintenance simulation results; represents the effectiveness weight coefficient of the i-th thermal control equipment performance index set in the simulation data; N represents that there are N thermal control equipment performance index sets in the simulation data; represents the effectiveness weight coefficient of the jth thermal control equipment performance indicator in the i-th thermal control equipment performance indicator set in the simulation data; represents the maintenance value of the jth thermal control device performance indicator in the i-th thermal control device performance indicator set in the VR scene; Indicates that there are a total of Thermal control equipment performance indicators; Represents the effectiveness weight coefficient of the non-parametric thermal control equipment performance index; NP represents the non-parametric thermal control equipment performance index; represents the effectiveness weight coefficient of the integrated performance value of the simulation data; EP represents the integrated performance value of the simulation data; F represents the comprehensive penalty function for maintaining the simulation operation; Z represents the comparative correlation function; Maintenance operation block: The effective value of the maintenance simulation result is compared with the preset effective value, and the thermal control equipment is maintained according to the maintenance simulation operation corresponding to the maintenance simulation result higher than the preset effective value.
[0011] The present invention provides a thermal control maintenance management system for a thermal power plant, a simulation block, and further includes: ,in, represents the weight coefficient of the kth penalty item; P represents the total number of penalty items; represents the kth penalty term in the maintenance simulation; represents the effectiveness weight coefficient of the qth regularity penalty; represents the qth regularity penalty in the maintenance simulation; Represents the effectiveness weight coefficient of the combination of empirical risk and basis function penalty; represents the effectiveness weight coefficient of the mth basis function penalty; B represents the total number of basis function penalties; represents the mth basis function penalty; Q represents the total number of regularity penalties; It represents the effectiveness weight coefficient of empirical risk; ER represents the empirical risk value of maintenance simulation; , where D represents the total number of data collection points; represents the validity weight coefficient of the log-likelihood and regularization term; Indicates the preset value of the nth data collection point in the VR scene and scene parameters Under the condition of , the output simulation value of the nth data collection point of the VR scene is The probability value of Scene parameters representing the VR scene; Indicates the input value for the nth data collection point in the VR scene The preset values made; Represents the input value of the nth data collection point in the VR scene; Represents the output simulation value of the nth data collection point in the VR scene; Represents the covariance of the output simulation values of the VR scene.
[0012] The present invention provides a thermal control maintenance management system for a thermal power plant, an optimization module, comprising: Adjustment unit: Evaluate the energy consumption of thermal control equipment according to the maintenance results, obtain the energy consumption evaluation results, formulate energy efficiency optimization strategies based on the energy consumption evaluation results, apply the energy efficiency optimization strategies to thermal control equipment, and make actual optimization adjustments; Update unit: monitors the operating status and energy consumption of the optimized thermal control equipment, evaluates the actual effect of the optimization strategy, improves the optimization strategy according to the effect evaluation results, feeds back the optimized data to the data acquisition module, and updates the data collection point information of the thermal control equipment.
[0013] Compared with the existing technology, the beneficial effects of this application are as follows: by analyzing the thermal control system requirements of thermal power plants, determining data collection points, collecting and analyzing equipment data, building a prediction model, using AR and VR technology for status identification and maintenance judgment, and finally optimizing energy management, the intelligence level of the thermal control system is improved, accurate fault diagnosis and prediction are achieved, and the level of energy efficiency management is improved, thereby ensuring power generation efficiency and safety.
[0014] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.
[0015] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural schematic diagram of a thermal control maintenance management system for a thermal power plant provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0017] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.
[0018] Embodiment 1: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, such as Figure 1 As shown, including: Data acquisition module: Analyze the actual needs of the thermal control system of the thermal power plant, determine the data collection points of the thermal control equipment of the thermal control system of the thermal power plant based on the actual needs, and obtain historical thermal control equipment data based on the data collection points; Model building module: Analyze historical thermal control equipment data to obtain fault-related features and energy efficiency-related features, filter and mark historical thermal control equipment data according to the fault-related features and energy efficiency-related features, obtain fault-related data and energy efficiency-related data, and build a prediction model based on data collection points and marking results; Maintenance module: Develop corresponding AR applications based on the prediction model, identify the current status of the thermal control equipment based on the AR application, create VR scenes based on the prediction model, make maintenance judgments on the current status of the thermal control equipment based on the VR scenes, and maintain the thermal control equipment; Optimization module: Optimize energy management of thermal control equipment based on maintenance results.
[0019] In this embodiment, the input of the prediction model refers to the data used to train and run the prediction model. These data usually come from the processing results of the feature extraction unit and the data extraction unit. The input includes fault-related data, energy efficiency-related data, and labels of data collection points: the third label indicates the characteristics and importance of the data collection point; the output of the prediction model refers to the results obtained after the prediction model is calculated and analyzed. These results are used to guide actual equipment maintenance and energy efficiency optimization. The output includes fault prediction results and energy efficiency optimization suggestions; the role of the prediction model is through analysis and processing of the input data.
[0020] In this embodiment, actual needs refer to specific needs that need to be met by the thermal control system of a thermal power plant, determined based on functional evaluation results and related technologies. For example, actual needs may include improving the real-time performance of data collection, enhancing the system's fault prediction capabilities, optimizing energy management efficiency, etc.
[0021] In this embodiment, the data collection points refer to the specific locations where sensors and monitoring equipment are deployed in the thermal control system of a thermal power plant. These locations will be used to collect historical thermal control equipment data. For example, temperature sensors are installed on the inlet and outlet pipes of the boiler and vibration sensors are installed on the bearings of the turbine.
[0022] In this embodiment, historical thermal control equipment data includes but is not limited to real-time monitoring data of parameters such as temperature, pressure, flow, vibration, speed, and other parameters, as well as information such as the working status and fault records of the equipment, for example, the temperature, pressure and fuel consumption data of the boiler, the speed, load and thermal efficiency data of the turbine, and the voltage, current and frequency data of the generator.
[0023] In this embodiment, fault-related characteristics may include abnormal temperature change rate, pressure fluctuation, vibration amplitude, etc. For example, the fault-related characteristics of the boiler control system are abnormal temperature change, pressure fluctuation, increased vibration, etc. These characteristics may indicate damage or wear of internal components of the boiler; energy efficiency-related characteristics may include heat utilization rate, fuel consumption rate, power generation efficiency, etc. For example, the energy efficiency-related characteristics of the generator control system are data such as the voltage, current, frequency, etc. of the generator. These characteristics can help optimize the energy consumption and efficiency of the generator.
[0024] In this embodiment, the current state of the thermal control device refers to the operating state of the thermal control device at a specific time point, including its operating parameters, performance indicators, and fault information.
[0025] In this embodiment, the maintenance judgment process is to perform virtual maintenance operations on the thermal control equipment in a VR scene, and judge whether the maintenance operation is effective based on the results of the maintenance operation and preset effectiveness standards. For effective maintenance operations, they are applied to actual thermal control equipment maintenance.
[0026] In this embodiment, by setting goals and refining functions, AR applications are arranged in combination with the actual environment and worker needs to display equipment status, VR scenes are built based on equipment status and historical data for maintenance simulation, and maintenance is implemented after the effectiveness of the simulation results is judged.
[0027] In this embodiment, the maintenance result refers to the result data of the maintenance operation on the thermal control equipment provided by the maintenance module. These data reflect the impact of the maintenance operation on the equipment performance and status, for example, the equipment operating parameters after the maintenance operation, such as the temperature, pressure, fuel consumption and other data of the boiler, and the effectiveness evaluation of the maintenance operation, such as the reduction of equipment failure rate and the extension of equipment life.
[0028] In this embodiment, the process of energy management optimization is to evaluate the maintenance result data of thermal control equipment, analyze energy consumption, formulate and implement energy efficiency optimization strategies, monitor the optimization effect, and finally adjust the optimization strategy and update the data collection point information according to the evaluation results.
[0029] The working principle and beneficial effects of the above technical solution are: by analyzing the needs of the thermal control system of the thermal power plant, determining the data collection points, collecting and analyzing equipment data, building a prediction model, using AR and VR technology for status identification and maintenance judgment, and finally optimizing energy management, the intelligence level of the thermal control system is improved, accurate fault diagnosis and prediction are achieved, and the level of energy efficiency management is improved, thereby ensuring power generation efficiency and safety.
[0030] Embodiment 2: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, a data acquisition module, including: Actual demand unit: conduct functional evaluation of thermal control systems of thermal power plants, obtain the functional evaluation results, understand the relevant technologies of thermal control systems of thermal power plants, and determine the actual needs of thermal control systems of thermal power plants by combining the functional evaluation results with relevant technologies; A collection point determination unit is configured to determine the type of data that needs to be collected according to the actual needs of the thermal control system of the thermal power plant, and to perform a first thermal control device classification on the thermal control equipment of the thermal control system of the thermal power plant using the function evaluation result. At the same time, the thermal control equipment is classified into a second thermal control device classification using the data type, and the data collection point of the thermal control equipment is determined based on the first thermal control device classification, and historical thermal control equipment data is collected at the data collection point according to the second thermal control device classification.
[0031] In this embodiment, functional evaluation refers to a detailed inspection and evaluation of the functions that the thermal control system of a thermal power plant needs to perform to ensure that the system can meet the operating requirements of the power plant. The specific process includes establishing a set of standards for evaluating the functions of the thermal control system of a thermal power plant, such as stability, efficiency, safety, etc., collecting the configuration, performance and operating data of the current thermal control system, analyzing the performance of the system in actual operation, identifying existing problems and deficiencies, and generating a functional evaluation report based on the evaluation results, outlining the advantages of the system and areas for improvement.
[0032] In this embodiment, relevant technologies refer to advanced technologies related to thermal control systems of thermal power plants that are currently on the market or in the research field. These technologies may include: advanced sensor technology, artificial intelligence and machine learning algorithms, Internet of Things (IoT) platforms, augmented reality (AR) and virtual reality (VR) technologies, etc.
[0033] In this embodiment, the functional evaluation results refer to the conclusions obtained after performing a functional evaluation on the thermal control system of a thermal power plant. These conclusions will be used to determine the actual needs of the system. For example, the evaluation report may point out that the existing thermal control system has delays in data collection and processing and requires more advanced sensors and data analysis tools.
[0034] In this embodiment, the data type refers to the specific type of data that needs to be collected from the thermal control system of the thermal power plant. These data types will be used to build prediction models and maintenance management systems, such as temperature data, pressure data, flow data, vibration data, and energy consumption data.
[0035] In this embodiment, the first thermal control device classification is based on the function and purpose of the thermal control device, which helps to determine the type of device that needs to collect data, for example, classification by function: sensor, actuator, controller, etc.
[0036] In this embodiment, the second thermal control device classification is based on the technical characteristics or data types of the thermal control devices, which helps to determine the detailed parameters and frequency of data collection, for example, classification by technical characteristics: wired sensors, wireless sensors, smart sensors, etc.
[0037] The working principle and beneficial effects of the above technical solution are: through functional evaluation and understanding of related technologies to clarify the actual needs of the thermal control system of the thermal power plant, and then based on these needs to determine the type of data to be collected and the corresponding thermal control equipment classification, and then determine the data collection points, and conduct data collection, to achieve accurate data collection and analysis, promote the intelligent and optimized operation of the thermal control system, thereby improving power generation efficiency and safety.
[0038] Embodiment 3: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, and a model building module, including: Feature extraction unit: According to the working principle and actual needs of each thermal control device, the fault feature analysis and energy efficiency feature analysis of the historical thermal control device data are performed respectively, and the fault-related features and energy efficiency-related features are listed; Data extraction unit: obtains the operation requirements of the thermal control equipment to derive the fault-related characteristics and the energy efficiency-related characteristics, obtains the fault-derived characteristics and the energy efficiency-derived characteristics, performs a first screening on the historical thermal control equipment data according to the fault correlation between the historical thermal control equipment data and the fault-derived characteristics, and first marks the first screening results to obtain the fault-related data, and at the same time, performs a second screening on the historical thermal control equipment data according to the energy efficiency correlation between the historical thermal control equipment data and the energy efficiency-derived characteristics, and second marks the second screening results to obtain the energy efficiency-related data; Prediction model unit: a third mark is performed on the data collection point based on the fault-related data and the energy efficiency-related data, and a prediction model is constructed according to the first mark, the second mark and the third mark.
[0039] In this embodiment, the historical thermal control equipment data includes the long-term operation data of the thermal control system of the thermal power plant, and these data are used for analysis, optimization and fault diagnosis.
[0040] In this embodiment, the working principle of the thermal control device involves thermodynamics, fluid mechanics and automatic control theory, and is mainly used to control parameters such as temperature and pressure in the thermal power generation process.
[0041] In this embodiment, fault feature analysis refers to identifying feature parameters that may cause equipment failure by analyzing historical thermal control equipment data; energy efficiency feature analysis refers to identifying feature parameters that affect the energy efficiency performance of thermal control equipment.
[0042] In this embodiment, energy efficiency correlation refers to the degree of correlation between historical thermal control equipment data and energy efficiency derived characteristics, which is used to measure the relationship between historical data and equipment energy efficiency performance. For example, the correlation between the energy consumption data of the turbine and energy efficiency derived characteristics such as turbine speed and load reflects the operating efficiency of the turbine; fault correlation refers to the degree of correlation between historical thermal control equipment data and fault derived characteristics, which is used to measure the relationship between historical data and the possibility of equipment failure. For example, the correlation between the temperature data of the boiler and fault derived characteristics such as boiler pressure and fuel consumption reflects the risk of boiler failure.
[0043] In this embodiment, the fault-derived feature is a feature further derived from the fault-related feature, such as the temperature trend before the fault, etc.; the energy efficiency-derived feature is derived from the energy efficiency-related feature, such as the energy efficiency change trend under different loads.
[0044] In this embodiment, the first screening is to screen the historical thermal control equipment data according to the fault-derived characteristics to identify potential fault data; the second screening is to screen the historical thermal control equipment data according to the energy efficiency-derived characteristics to identify data related to energy efficiency; the first screening result is a fault-related data set, and the second screening result is an energy efficiency-related data set.
[0045] In this embodiment, the first mark is to mark the screened fault-related data; the second mark is to mark the screened energy efficiency-related data; the third mark is to comprehensively mark the data collection points, which may involve composite marks of faults and energy efficiency. For example, the first mark of the boiler control system is to mark fault-related data such as abnormal temperature increase and pressure fluctuation for subsequent analysis and processing; the second mark of the turbine control system is to mark energy efficiency-related data such as thermal efficiency and speed for subsequent analysis and optimization; the third mark of the data collection point is to mark the data collection point according to the fault-related data and energy efficiency-related data for subsequent data collection and management.
[0046] The working principle and beneficial effects of the above technical solution are: by analyzing historical thermal control equipment data, extracting fault characteristics and energy efficiency characteristics, then deriving the characteristics, screening out fault-related data and energy efficiency-related data, and finally building a prediction model, it helps to improve the accuracy of fault diagnosis and prediction, realize refined management of thermal control equipment, and improve power generation efficiency and safety.
[0047] Embodiment 4: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, the maintenance module comprising: Acquire functional units: set the overall goal of the thermal control system of the thermal power plant according to the actual needs of the thermal control system of the thermal power plant, list the first basic functions of the AR application based on the overall goal, refine the first basic functions according to the detailed function table, and obtain the first function to be realized; AR unit: obtaining the actual operating environment of the thermal control equipment of the thermal power plant and the use of the thermal control equipment in the actual operating environment, determining the worker demand based on the actual operating environment and the use of the thermal control equipment, arranging the scene for the AR application according to the prediction result output by the prediction model combined with the worker demand and the first function to be realized, forming an AR application, and outputting the current state of the thermal control equipment of the thermal control equipment based on the AR application; VR unit: based on the overall goal, lists the second basic functions of the VR application, extracts maintenance-related data from the historical thermal control device data according to the current state of the thermal control device, and combines the second basic functions with the maintenance-related data to form a VR scene; Judgment unit: Make maintenance judgments on the corresponding thermal control equipment based on the VR scene, and perform maintenance simulation on the thermal control equipment in the VR scene. Make validity judgments on the maintenance simulation results based on maintenance-related data, and perform actual operations on the maintenance simulation results that are higher than the preset effective values to maintain the thermal control equipment.
[0048] In this embodiment, the process of setting overall goals based on actual needs is to analyze the actual needs of the thermal control system of the thermal power plant, such as equipment maintenance, fault diagnosis, energy efficiency management, etc., and determine the overall goals that the system needs to achieve, such as improving maintenance efficiency, reducing downtime, and enhancing safety.
[0049] In this embodiment, the first basic function refers to the basic functions that the AR application needs to implement, which are necessary to meet the overall goal, such as displaying a 3D model of the thermal control equipment, providing real-time data on the equipment status, etc.
[0050] In this embodiment, the detailed function description table is a document that refines the first basic function. It describes in detail the implementation method and expected effect of each function. For example, the first basic function is fault diagnosis, and the corresponding function description is to analyze and diagnose the fault of the thermal control equipment. The corresponding first function to be implemented in the AR application is to quickly locate the cause of the fault and improve the efficiency of equipment maintenance.
[0051] In this embodiment, the actual operating environment refers to the actual operating environment of the thermal control equipment of a thermal power plant, including the physical location of the equipment, the surrounding environment, the working conditions, etc. For example, the boiler room: high temperature, high pressure, noisy, and limited space; the turbine room: needs to be kept clean, constant temperature, and constant humidity.
[0052] In this embodiment, the use of thermal control equipment refers to the specific situation of workers using thermal control equipment in the actual operating environment, including the equipment's operating time, frequency of use, maintenance, etc. For example, boilers: need to regularly check combustion conditions, clean slag, and monitor water quality; turbines: need to regularly check lubricating oil, cooling water, and monitor vibration.
[0053] In this embodiment, the first function to be implemented is a function list refined according to the detailed function description table. These functions will be specific goals of AR application development, for example, displaying real-time operating data of thermal control equipment in the AR interface, such as temperature, pressure, flow, etc.
[0054] In this embodiment, the worker needs are derived by comprehensively considering the environmental impact needs and potential maintenance needs. These needs together constitute the comprehensive needs of workers when operating thermal control equipment. For example, workers may need to operate equipment in a high temperature environment and need to regularly check the cooling system of the equipment to ensure the normal operation of the equipment.
[0055] In this embodiment, the process of scene arrangement is to design the interface and interaction of the AR application according to the needs of the workers and the first function to be realized, combine the AR application with the actual operating environment, ensure that the application can work effectively in the real environment, and integrate the prediction results output by the prediction model to provide real-time information on the equipment status, such as an AR application for displaying a 3D model of a boiler and providing real-time temperature and pressure data.
[0056] In this embodiment, the second basic function refers to the basic functions that the VR application needs to implement, which are necessary to meet the overall goal, such as simulating the maintenance process of thermal control equipment, providing a virtual diagnosis environment for equipment failures, and realizing virtual training for equipment operation.
[0057] In this embodiment, maintenance-related data refers to data related to maintenance operations of thermal control equipment, such as historical maintenance records, fault diagnosis data, equipment operation manuals, etc.
[0058] In this embodiment, the specific process of forming a VR scene is to design the layout and interaction of the VR scene according to the second basic function and maintenance-related data, use 3D modeling technology to create a virtual model of the thermal control equipment, and integrate the maintenance data in the historical thermal control equipment data to provide real-time information on the equipment status. For example, a VR scene that simulates the turbine maintenance process allows workers to practice operations in a virtual environment.
[0059] The working principle and beneficial effects of the above technical solution are: by setting goals and refining functions, AR applications are arranged in combination with the actual environment and workers' needs to display the equipment status, VR scenes are built based on the equipment status and historical data for maintenance simulation, and maintenance is implemented after the effectiveness of the simulation results is judged. Through AR and VR technology, intuitive monitoring and simulated maintenance of thermal control equipment are achieved, which improves the intelligence and safety of the thermal control system.
[0060] Embodiment 5: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, an AR unit, including: Worker demand block: Analyze the actual operating environment of thermal control equipment in thermal power plants, evaluate the impact of the actual operating environment on worker operations, and derive environmental impact requirements. At the same time, collect the use of thermal control equipment for each thermal control equipment in the actual operating environment, analyze the use of thermal control equipment, determine the potential maintenance requirements of the corresponding thermal control equipment, and combine the environmental impact requirements and potential maintenance requirements to derive worker requirements. Current status block: further refine the worker needs according to the output results of the prediction model, clarify the safety requirements of the workers in different actual operating environments based on the refined worker needs, arrange the AR application scene in combination with the refined worker needs, safety requirements and the first function to be implemented, and output the current status of the thermal control equipment based on the AR application.
[0061] In this embodiment, environmental impact requirements refer to the impact of the actual operating environment on workers' operations. These requirements are usually related to the health, safety, and comfort of workers. For example, workers working in a high temperature environment may need cooling equipment or appropriate rest time, and workers working in a noisy environment may need hearing protection equipment.
[0062] In this embodiment, potential maintenance requirements refer to failures and maintenance requirements that may occur during the operation of the thermal control equipment. These requirements are usually related to the reliability, efficiency and life of the equipment, such as regularly checking and replacing the lubricating oil of the equipment and monitoring the vibration level of the equipment to prevent potential mechanical failures.
[0063] In this embodiment, the process of refining worker needs is to analyze the specific impact of the actual operating environment on workers, collect and analyze the usage of thermal control equipment, identify potential maintenance needs of equipment, comprehensively consider environmental impacts and potential maintenance needs, and clarify the specific needs of workers under different working conditions.
[0064] In this embodiment, safety requirements refer to safety requirements that workers must meet when operating thermal control equipment. These requirements are usually related to the equipment's operating procedures, safety standards, and laws and regulations. For example, workers need to wear appropriate personal protective equipment, such as safety helmets, protective glasses, earplugs, etc., and workers need to comply with safety operating procedures, such as using ladders correctly and avoiding contact with live parts.
[0065] The working principle and beneficial effects of the above technical solution are: by analyzing the environment and equipment usage to determine worker needs, refining safety requirements based on predictive model output and worker needs, and displaying the current status of the equipment through AR applications to meet actual operational needs, the working environment and maintenance process of thermal control equipment in thermal power plants are optimized, the accuracy and safety of workers' operations are improved, and the overall operation and maintenance level of the thermal control system is improved.
[0066] Embodiment 6: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, wherein the judgment unit comprises: Judgment block: obtain the real-time status data of the thermal control equipment in the VR scene, compare the maintenance-related data with the real-time status data, and determine whether the corresponding thermal control equipment needs maintenance based on the comparison results; Simulation block: If maintenance is required, the corresponding maintenance simulation operation is obtained according to the maintenance-related data, the maintenance simulation operation is performed on the corresponding thermal control equipment in the VR scene, the simulation data during the maintenance simulation operation is collected, and the effective value of the maintenance simulation result is calculated according to the simulation data: , where V represents the validity function of the maintenance simulation results; represents the effectiveness weight coefficient of the i-th thermal control equipment performance index set in the simulation data; N represents that there are N thermal control equipment performance index sets in the simulation data; represents the effectiveness weight coefficient of the jth thermal control equipment performance indicator in the i-th thermal control equipment performance indicator set in the simulation data; represents the maintenance value of the jth thermal control device performance indicator in the i-th thermal control device performance indicator set in the VR scene; Indicates that there are a total of Thermal control equipment performance indicators; Represents the effectiveness weight coefficient of the non-parametric thermal control equipment performance index; NP represents the non-parametric thermal control equipment performance index; represents the effectiveness weight coefficient of the integrated performance value of the simulation data; EP represents the integrated performance value of the simulation data; F represents the comprehensive penalty function for maintaining the simulation operation; Z represents the comparative correlation function; Maintenance operation block: The effective value of the maintenance simulation result is compared with the preset effective value, and the thermal control equipment is maintained according to the maintenance simulation operation corresponding to the maintenance simulation result higher than the preset effective value.
[0067] In this embodiment, real-time status data refers to the operating status data of the thermal control equipment at the current moment. These data reflect the immediate performance and status of the equipment, such as the real-time temperature, pressure, fuel consumption and other data of the boiler, the real-time speed, load, thermal efficiency and other data of the turbine, and the real-time voltage, current, frequency and other data of the generator.
[0068] In this embodiment, the thermal control equipment performance indicator set refers to a group of indicators used to evaluate the performance of the thermal control equipment. These indicators together constitute a comprehensive evaluation of the equipment performance. For example, the performance indicator set of a boiler may include indicators such as temperature, pressure, and combustion efficiency, and the performance indicator set of a turbine may include indicators such as speed, load, thermal efficiency, and vibration level.
[0069] In this embodiment, the thermal control equipment performance index refers to a single index used to evaluate the performance of the thermal control equipment. These indicators can reflect the performance of the equipment from different angles, such as temperature: the furnace temperature of the boiler, the exhaust temperature of the turbine, etc., pressure: the steam pressure of the boiler, the steam inlet pressure of the turbine, etc., combustion efficiency: the ratio of the heat generated by the boiler burning fuel to the fuel input heat.
[0070] In this embodiment, the maintenance value of the jth thermal control device performance indicator in the i-th thermal control device performance indicator set refers to the value reached by the jth performance indicator in the i-th performance indicator set after the maintenance operation is simulated in the VR scene. For example, after the maintenance operation of the boiler is simulated in the VR scene, the furnace temperature of the boiler reaches the set maintenance value.
[0071] In this embodiment, the integrated performance value refers to the overall evaluation value of the performance of the thermal control equipment after comprehensively considering multiple performance indicators. For example, after comprehensively considering multiple performance indicators such as the temperature, pressure, and combustion efficiency of the boiler, the overall performance of the boiler is evaluated and the value is obtained.
[0072] In this embodiment, the non-parametric thermal control device performance indicator is a thermal control device performance indicator that is not defined by a parameterized model, such as the temperature control capability, energy consumption, system response speed, etc. of the device.
[0073] In this embodiment, the comprehensive penalty function includes factors such as different dimensional weights, empirical risks, basis functions, etc., and is a formula derived from the weight coefficients, basis function penalties, and other empirical risks.
[0074] In this embodiment, the comparison correlation function represents the comparison result between the output simulation value obtained after inputting the actual data in the VR scene and the preset value of the corresponding data collection point.
[0075] The working principle and beneficial effects of the above technical solution are: by comparing the real-time status data and maintenance-related data in the VR scene to determine the maintenance needs, executing maintenance simulation operations and calculating the effectiveness value, and deciding whether to implement actual maintenance operations based on the effective value of the simulation results, the intelligent monitoring and predictive maintenance capabilities of the thermal control system are improved, thereby ensuring power generation efficiency and operational safety.
[0076] Embodiment 7: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, the simulation block also includes: ,in, represents the weight coefficient of the kth penalty item; P represents the total number of penalty items; represents the kth penalty term in the maintenance simulation; represents the effectiveness weight coefficient of the qth regularity penalty; represents the qth regularity penalty in the maintenance simulation; Represents the effectiveness weight coefficient of the combination of empirical risk and basis function penalty; represents the effectiveness weight coefficient of the mth basis function penalty; B represents the total number of basis function penalties; represents the mth basis function penalty; Q represents the total number of regularity penalties; It represents the effectiveness weight coefficient of empirical risk; ER represents the empirical risk value of maintenance simulation; , where D represents the total number of data collection points; represents the validity weight coefficient of the log-likelihood and regularization term; Indicates the preset value of the nth data collection point in the VR scene and scene parameters Under the condition of , the output simulation value of the nth data collection point of the VR scene is The probability value of Scene parameters representing the VR scene; Indicates the input value for the nth data collection point in the VR scene The preset values made; Represents the input value of the nth data collection point in the VR scene; Represents the output simulation value of the nth data collection point in the VR scene; Represents the covariance of the output simulation values of the VR scene.
[0077] In this embodiment, the scene parameters of the VR scene refer to the parameters that need to be considered when simulating the maintenance operation of thermal control equipment in a virtual reality environment. These parameters will affect the accuracy and effect of the simulation, including: the current status of the equipment: such as real-time data such as the temperature and pressure of the boiler, the specific steps of the maintenance operation: such as cleaning, inspection, replacement of parts, etc., the workers' operating environment: such as temperature, humidity, lighting, etc., the specifications and models of the equipment: such as the capacity of the boiler, the type of turbine, etc.
[0078] In this embodiment, the empirical risk value of the maintenance simulation refers to the possible deviation between the simulation result and the actual situation due to various uncertain factors (such as aging of equipment, skill level of the operator, etc.) when simulating maintenance operations in a VR scene.
[0079] In this embodiment, the preset value is the input value of the nth data collection point Maps to a preset value.
[0080] The working principle and beneficial effects of the above technical solution are: by analyzing the real-time status and maintenance data of the equipment, executing simulated maintenance and calculating the effectiveness value, and performing actual maintenance based on the comparison results between the effectiveness value and the preset threshold, the intelligent level of maintenance of thermal control equipment in thermal power plants is improved, manual intervention is reduced, and the accuracy and efficiency of maintenance are improved.
[0081] Embodiment 8: The embodiment of the present invention provides a thermal control maintenance management system for a thermal power plant, an optimization module, including: Adjustment unit: Evaluate the energy consumption of thermal control equipment according to the maintenance results, obtain the energy consumption evaluation results, formulate energy efficiency optimization strategies based on the energy consumption evaluation results, apply the energy efficiency optimization strategies to thermal control equipment, and make actual optimization adjustments; Update unit: monitors the operating status and energy consumption of the optimized thermal control equipment, evaluates the actual effect of the optimization strategy, improves the optimization strategy according to the effect evaluation results, feeds back the optimized data to the data acquisition module, and updates the data collection point information of the thermal control equipment.
[0082] In this embodiment, energy consumption refers to the energy consumed by the thermal control equipment during operation. These data reflect the energy efficiency level of the equipment, such as the fuel consumption of the boiler, the power consumption of the turbine, the cooling water consumption of the generator, etc.
[0083] In this embodiment, the energy efficiency optimization strategy refers to a strategy for improving the energy efficiency of thermal control equipment developed based on the energy consumption assessment results, such as adjusting the combustion parameters of the boiler to reduce fuel consumption and optimizing the operating parameters of the turbine to improve thermal efficiency.
[0084] In this embodiment, the effect evaluation result refers to the conclusion of evaluating the actual effect of the optimization strategy based on the effect monitoring result.
[0085] In this embodiment, improvement refers to the adjustment and optimization of the optimization strategy based on the effect evaluation results to improve the efficiency and effectiveness of the strategy. For example, if the monitoring results show that the fuel consumption has not decreased significantly, it may be necessary to further adjust the boiler's combustion parameters or consider replacing more efficient combustion equipment.
[0086] The working principle and beneficial effects of the above technical solution are: by evaluating the maintenance result data of thermal control equipment, analyzing energy consumption, formulating and implementing energy efficiency optimization strategies, monitoring the optimization effects, and finally adjusting the optimization strategies and updating the data collection point information according to the evaluation results, the intelligence level of the thermal control system is improved, the stability and reliability of the system are enhanced, and the power generation efficiency and safety are ensured.
[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A thermal control maintenance management system for a thermal power plant, characterized in that: include: Data acquisition module: Analyze the actual needs of the thermal control system of the thermal power plant, determine the data collection points of the thermal control equipment of the thermal control system of the thermal power plant based on the actual needs, and obtain historical thermal control equipment data based on the data collection points; Model building module: Analyze historical thermal control equipment data to obtain fault-related features and energy efficiency-related features, filter and mark historical thermal control equipment data according to the fault-related features and energy efficiency-related features, obtain fault-related data and energy efficiency-related data, and build a prediction model based on data collection points and marking results; Maintenance module: Develop corresponding AR applications based on the prediction model, identify the current status of the thermal control equipment based on the AR application, create VR scenes based on the prediction model, make maintenance judgments on the current status of the thermal control equipment based on the VR scenes, and maintain the thermal control equipment; Optimization module: Optimize energy management of thermal control equipment based on maintenance results.
2. A thermal control maintenance management system for a thermal power plant according to claim 1, characterized in that: Data acquisition module, including: Actual demand unit: conduct functional evaluation of thermal control systems of thermal power plants, obtain the functional evaluation results, understand the relevant technologies of thermal control systems of thermal power plants, and determine the actual needs of thermal control systems of thermal power plants by combining the functional evaluation results with relevant technologies; A collection point determination unit is configured to determine the type of data that needs to be collected according to the actual needs of the thermal control system of the thermal power plant, and to perform a first thermal control device classification on the thermal control equipment of the thermal control system of the thermal power plant using the function evaluation result. At the same time, the thermal control equipment is classified into a second thermal control device classification using the data type, and the data collection point of the thermal control equipment is determined based on the first thermal control device classification, and historical thermal control equipment data is collected at the data collection point according to the second thermal control device classification.
3. A thermal control maintenance management system for a thermal power plant according to claim 2, characterized in that: Model building modules, including: Feature extraction unit: According to the working principle and actual needs of each thermal control device, the fault feature analysis and energy efficiency feature analysis of the historical thermal control device data are performed respectively, and the fault-related features and energy efficiency-related features are listed; Data extraction unit: obtains the operation requirements of the thermal control equipment to derive the fault-related characteristics and the energy efficiency-related characteristics, obtains the fault-derived characteristics and the energy efficiency-derived characteristics, performs a first screening on the historical thermal control equipment data according to the fault correlation between the historical thermal control equipment data and the fault-derived characteristics, and first marks the first screening results to obtain the fault-related data, and at the same time, performs a second screening on the historical thermal control equipment data according to the energy efficiency correlation between the historical thermal control equipment data and the energy efficiency-derived characteristics, and second marks the second screening results to obtain the energy efficiency-related data; Prediction model unit: a third mark is performed on the data collection point based on the fault-related data and the energy efficiency-related data, and a prediction model is constructed according to the first mark, the second mark and the third mark.
4. A thermal control maintenance management system for a thermal power plant according to claim 1, characterized in that: Maintenance module, including: Acquire functional units: set the overall goal of the thermal control system of the thermal power plant according to the actual needs of the thermal control system of the thermal power plant, list the first basic functions of the AR application based on the overall goal, refine the first basic functions according to the detailed function table, and obtain the first function to be realized; AR unit: obtaining the actual operating environment of the thermal control equipment of the thermal power plant and the use of the thermal control equipment in the actual operating environment, determining the worker demand based on the actual operating environment and the use of the thermal control equipment, arranging the scene for the AR application according to the prediction result output by the prediction model combined with the worker demand and the first function to be realized, forming an AR application, and outputting the current state of the thermal control equipment of the thermal control equipment based on the AR application; VR unit: based on the overall goal, lists the second basic functions of the VR application, extracts maintenance-related data from the historical thermal control device data according to the current state of the thermal control device, and combines the second basic functions with the maintenance-related data to form a VR scene; Judgment unit: Make maintenance judgments on the corresponding thermal control equipment based on the VR scene, and perform maintenance simulation on the thermal control equipment in the VR scene. Make validity judgments on the maintenance simulation results based on maintenance-related data, and perform actual operations on the maintenance simulation results that are higher than the preset effective values to maintain the thermal control equipment.
5. A thermal control maintenance management system for a thermal power plant according to claim 4, characterized in that: AR unit, including: Worker demand block: Analyze the actual operating environment of thermal control equipment in thermal power plants, evaluate the impact of the actual operating environment on worker operations, and derive environmental impact requirements. At the same time, collect the use of thermal control equipment for each thermal control equipment in the actual operating environment, analyze the use of thermal control equipment, determine the potential maintenance requirements of the corresponding thermal control equipment, and combine the environmental impact requirements and potential maintenance requirements to derive worker requirements. Current status block: further refine the worker needs according to the output results of the prediction model, clarify the safety requirements of the workers in different actual operating environments based on the refined worker needs, arrange the AR application scene in combination with the refined worker needs, safety requirements and the first function to be implemented, and output the current status of the thermal control equipment based on the AR application.
6. A thermal control maintenance management system for a thermal power plant according to claim 4, characterized in that: The judgment unit comprises: Judgment block: obtain the real-time status data of the thermal control equipment in the VR scene, compare the maintenance-related data with the real-time status data, and determine whether the corresponding thermal control equipment needs maintenance based on the comparison results; Simulation block: If maintenance is required, the corresponding maintenance simulation operation is obtained according to the maintenance-related data, the maintenance simulation operation is performed on the corresponding thermal control equipment in the VR scene, the simulation data during the maintenance simulation operation is collected, and the effective value of the maintenance simulation result is calculated according to the simulation data: , where V represents the validity function of the maintenance simulation results; represents the effectiveness weight coefficient of the i-th thermal control equipment performance index set in the simulation data; N represents that there are N thermal control equipment performance index sets in the simulation data; represents the effectiveness weight coefficient of the jth thermal control equipment performance indicator in the i-th thermal control equipment performance indicator set in the simulation data; represents the maintenance value of the jth thermal control device performance indicator in the i-th thermal control device performance indicator set in the VR scene; Indicates that there are a total of Thermal control equipment performance indicators; Represents the effectiveness weight coefficient of the non-parametric thermal control equipment performance index; NP represents the non-parametric thermal control equipment performance index; represents the effectiveness weight coefficient of the integrated performance value of the simulation data; EP represents the integrated performance value of the simulation data; F represents the comprehensive penalty function for maintaining the simulation operation; Z represents the comparative correlation function; Maintenance operation block: The effective value of the maintenance simulation result is compared with the preset effective value, and the thermal control equipment is maintained according to the maintenance simulation operation corresponding to the maintenance simulation result higher than the preset effective value.
7. A thermal control maintenance management system for a thermal power plant according to claim 6, characterized in that: Simulation blocks also include: ,in, represents the weight coefficient of the kth penalty item; P represents the total number of penalty items; represents the kth penalty term in the maintenance simulation; represents the effectiveness weight coefficient of the qth regularity penalty; represents the qth regularity penalty in the maintenance simulation; Represents the effectiveness weight coefficient of the combination of empirical risk and basis function penalty; represents the effectiveness weight coefficient of the mth basis function penalty; B represents the total number of basis function penalties; represents the mth basis function penalty; Q represents the total number of regularity penalties; It represents the effectiveness weight coefficient of empirical risk; ER represents the empirical risk value of maintenance simulation; , where D represents the total number of data collection points; represents the validity weight coefficient of the log-likelihood and regularization term; Indicates the preset value of the nth data collection point in the VR scene and scene parameters Under the condition of , the output simulation value of the nth data collection point of the VR scene is The probability value of Scene parameters representing the VR scene; Indicates the input value for the nth data collection point in the VR scene The preset values made; Represents the input value of the nth data collection point in the VR scene; Represents the output simulation value of the nth data collection point in the VR scene; Represents the covariance of the output simulation values of the VR scene.
8. A thermal control maintenance management system for a thermal power plant according to claim 3, characterized in that: Optimization modules, including: Adjustment unit: Evaluate the energy consumption of thermal control equipment according to the maintenance results, obtain the energy consumption evaluation results, formulate energy efficiency optimization strategies based on the energy consumption evaluation results, apply the energy efficiency optimization strategies to thermal control equipment, and make actual optimization adjustments; Update unit: monitors the operating status and energy consumption of the optimized thermal control equipment, evaluates the actual effect of the optimization strategy, improves the optimization strategy according to the effect evaluation results, feeds back the optimized data to the data acquisition module, and updates the data collection point information of the thermal control equipment.