Health management prediction system based on full life cycle of power high-voltage circuit breaker equipment

Abstract

The invention provides a health management prediction system based on a full life cycle of electric power high-voltage circuit breaker equipment, and relates to the technical field of electric power equipment health management, comprising the steps of collecting original single-dimensional index data of the electric power high-voltage circuit breaker equipment and preprocessing the original single-dimensional index data to generate target single-dimensional index data; calculating a single-dimensional health index score based on a single-dimensional index evaluation model, calculating an independent equipment health score based on a multi-dimensional health evaluation model, and calculating a comprehensive equipment health score based on a comprehensive health evaluation model; inputting the comprehensive equipment health score into an equipment fault prediction model to generate an equipment fault prediction result; acquiring equipment operation data, determining a comprehensive equipment maintenance score based on the equipment maintenance evaluation model, and generating an equipment maintenance suggestion; and an output result is sent to a user interaction display interface, so that the operation state of the high-voltage circuit breaker equipment can be monitored in real time, equipment faults can be found in time, safe operation of the equipment is ensured, and the management level and the operation efficiency of the equipment are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment health management, and in particular to a health management prediction system based on the full life cycle of power high-voltage circuit breaker equipment. Background Art

[0002] In the electric power industry, high-voltage circuit breaker equipment occupies an important position in the power grid. Sudden abnormal operation of circuit breaker equipment, such as failure or untimely opening, may cause the equipment to be damaged by high-voltage electricity or even cause serious fire.

[0003] Traditional equipment maintenance methods mainly rely on regular inspections and emergency response after failures. This method is unable to collect equipment operation data in real time and achieve comprehensive monitoring and prediction of equipment health status, which leads to inefficient equipment management. At the same time, this method is difficult to detect potential failures in advance, which can easily reduce the service life of equipment, cause equipment damage, and even cause serious accidents.

[0004] Therefore, it is necessary to provide a health management prediction system based on the entire life cycle of power high-voltage circuit breaker equipment to solve the above technical problems. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a health management prediction system based on the entire life cycle of electric high-voltage circuit breaker equipment, which is used to solve the problem that traditional equipment maintenance methods mainly rely on regular maintenance and emergency processing after failures, and cannot collect equipment operation data in real time and realize comprehensive monitoring and prediction of equipment health status, which leads to low equipment management efficiency. At the same time, it is difficult to detect potential faults in advance, which easily reduces the service life of the equipment, causes equipment damage, and even causes serious accidents.

[0006] The present invention provides a health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment, the prediction system comprising: The data acquisition and preprocessing module is used to acquire the original single-dimensional index data of the power high-voltage circuit breaker equipment in real time, and preprocess the original single-dimensional index data to generate target single-dimensional index data; A comprehensive health score calculation module, used to calculate the single-dimensional health index score corresponding to the target single-dimensional index data based on the single-dimensional index evaluation model, calculate the independent equipment health score of the electric high-voltage circuit breaker equipment according to the single-dimensional health index score based on the multi-dimensional health evaluation model, and calculate the comprehensive equipment health score according to the independent equipment health scores of all the electric high-voltage circuit breaker equipment based on the comprehensive health evaluation model; An equipment failure prediction module is used to construct an equipment failure prediction model and input the comprehensive equipment health score into the equipment failure prediction model to generate an equipment failure prediction result; An equipment maintenance suggestion generation module is used to obtain equipment operation data, combine the equipment failure prediction results, determine a comprehensive equipment maintenance score based on an equipment maintenance evaluation model, and generate corresponding equipment maintenance suggestions according to the comprehensive equipment maintenance score; The result sending and display module is used to send the comprehensive equipment health score, the equipment failure prediction result and the equipment maintenance suggestion to the user interaction display interface.

[0007] Preferably, the data acquisition and preprocessing module is used to collect original single-dimensional index data of the power high-voltage circuit breaker equipment in real time, and preprocess the original single-dimensional index data to generate target single-dimensional index data, specifically including: A data acquisition unit, used to collect the original single-dimensional indicator data in real time through a sensor network on the power high-voltage circuit breaker device, and the original single-dimensional indicator data includes original operating time, original opening times, original closing times and original energy storage times; A data cleaning unit, used to clean the original single-dimensional indicator data, remove noise data, abnormal data and duplicate data in the original single-dimensional indicator data, and generate corresponding intermediate single-dimensional indicator data; The data normalization unit is used to perform normalization processing on the intermediate single-dimensional indicator data to generate the corresponding target single-dimensional indicator data.

[0008] Preferably, the calculating of the single-dimensional health indicator score corresponding to the target single-dimensional indicator data based on the single-dimensional indicator evaluation model specifically includes: The target single-dimensional indicator data includes target operating time, target opening times, target closing times and target energy storage times; Obtaining the operating time parameter, the number of openings parameter, the number of closings parameter, the number of energy storage parameters and the number of historical faults of the electric high-voltage circuit breaker equipment, wherein the operating time parameter includes the historical operating time and the preset operating life time; the number of openings parameter includes the historical number of openings and the preset number of opening lifespans; the number of closings parameter includes the historical number of closings and the preset number of closing lifespans; the energy storage number parameter includes the historical number of energy storages and the preset number of energy storage lifespans; Based on the single-dimensional indicator evaluation model, the operating life score of the power high-voltage circuit breaker equipment is calculated according to the target operating time, the number of historical failures, the historical operating time and the preset operating life time. The corresponding calculation formula is as follows: In the formula, represents the operating life fraction; Indicates the weight corresponding to the operating life score; Indicates the target runtime; Indicates the preset operating life time; represents the operational failure fraction; Indicates the weight corresponding to the operation fault score; Indicates the historical running time; Indicates the number of historical faults; The operation score that represents the correlation between the historical operation time and the historical failure number; represents the runtime life fraction; According to the target number of openings, the number of historical faults, the number of historical openings and the preset number of opening lifespans, the opening number lifespan score of the power high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, Indicates the breaking life fraction; Indicates the weight corresponding to the trip life score; Indicates the target number of trips; Indicates the preset number of opening life times; Indicates the breaking fault fraction; Indicates the weight corresponding to the trip fault score; Indicates the number of historical opening times; Indicates the number of historical faults; Indicates the correlation between the historical tripping times and the historical fault times; Indicates the life fraction of the number of trips; According to the target closing times, the historical fault times, the historical closing times and the preset closing life times, the closing times life score of the electric high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, Indicates the closing life fraction; Indicates the weight corresponding to the closing life score; Indicates the target closing times; Indicates the preset closing life times; Indicates the closing fault fraction; Indicates the weight corresponding to the closing fault score; Indicates the historical closing times; Indicates the number of historical faults; The closing score that represents the historical closing times and the historical fault times; Indicates the life fraction of the number of closing times; According to the target energy storage times, the historical fault times, the historical energy storage times and the preset energy storage life times, the energy storage times life score of the electric high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, represents the energy storage life fraction; Represents the weight corresponding to the energy storage life score; Indicates the target energy storage times; Indicates the preset energy storage life times; represents the energy storage fault fraction; represents the weight corresponding to the energy storage fault score; Indicates the historical energy storage times; Indicates the number of historical faults; The energy storage score representing the correlation between the historical energy storage times and the historical fault times; Indicates the energy storage times life fraction; The single-dimensional health indicator score is obtained by summarizing the operating time life score, the opening times life score, the closing times life score and the energy storage times life score.

[0009] Preferably, the independent device health score of the electric high-voltage circuit breaker device is calculated according to the single-dimensional health indicator score based on the multi-dimensional health assessment model, and the corresponding calculation formula is as follows: In the formula, Indicates the health score of an individual device; represents the runtime life fraction; Indicates the life fraction of the number of trips; Indicates the life fraction of the number of closing times; Indicates the energy storage times life fraction; Indicates the weight corresponding to the runtime life fraction; Indicates the weight corresponding to the life score of the number of trips; Indicates the weight corresponding to the life score of the number of closing times; Indicates the weight corresponding to the energy storage times life score.

[0010] Preferably, the comprehensive equipment health score is calculated based on the comprehensive health assessment model according to the independent equipment health scores of all the electric high-voltage circuit breaker equipment, and the corresponding calculation formula is as follows: In the formula, Indicates the overall device health score; Indicates the total number of power high voltage circuit breaker equipment; represents the independent equipment health score of the mth power high voltage circuit breaker equipment; Represents the weight corresponding to the independent device health score of the mth power high-voltage circuit breaker device.

[0011] Preferably, the equipment failure prediction module is used to construct an equipment failure prediction model, and input the comprehensive equipment health score into the equipment failure prediction model to generate an equipment failure prediction result, specifically including: The comprehensive equipment health score is input into the equipment failure prediction model. The calculation formula of the forget gate of the equipment failure prediction model is as follows: In the formula, Represents the output of the forget gate at the current time t; Represents the weight corresponding to the forget gate; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of Represents the bias item corresponding to the forget gate; Represents the activation function.

[0012] Preferably, the calculation formula of the input gate of the equipment failure prediction model is as follows: In the formula, Represents the output of the input gate at the current time t; Represents the candidate memory unit at the current time t; and Represent the weights corresponding to the input gate and the candidate memory unit respectively; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of and Represent the bias items corresponding to the input gate and the candidate memory unit respectively; represents the activation function; represents the hyperbolic tangent function.

[0013] Preferably, the calculation formula for updating the memory unit of the equipment failure prediction model is as follows: In the formula, Represents the memory unit at the current time t; Represents the output of the forget gate at the current time t; Represents the memory unit at the previous time t-1; Represents the output of the input gate at the current time t; Represents the candidate memory unit at the current time t.

[0014] Preferably, the calculation formula of the output gate of the equipment failure prediction model is as follows: In the formula, represents the output of the output gate at the current time t; represents the activation function; Represents the weight corresponding to the output gate; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of Represents the bias term corresponding to the output gate; represents the hidden state at the current time t; represents the hyperbolic tangent function; Represents the memory unit at the current time t; The output of the output gate of the equipment failure prediction model is the equipment failure prediction result.

[0015] Preferably, each fault type in the equipment fault prediction result corresponds to a different preset fault code.

[0016] Compared with the related art, the health management prediction system based on the whole life cycle of electric high-voltage circuit breaker equipment provided by the present invention has the following beneficial effects: The present invention includes a data acquisition and preprocessing module, a comprehensive health score calculation module, an equipment failure prediction module, an equipment maintenance suggestion generation module and a result sending and display module. The original single-dimensional indicator data of the electric high-voltage circuit breaker equipment is collected in real time, and the original single-dimensional indicator data is preprocessed to generate target single-dimensional indicator data; the single-dimensional health indicator score corresponding to the target single-dimensional indicator data is calculated based on the single-dimensional indicator evaluation model, the independent equipment health score of the electric high-voltage circuit breaker equipment is calculated according to the single-dimensional health indicator score based on the multi-dimensional health evaluation model, and the comprehensive equipment health score is calculated according to the independent equipment health scores of all electric high-voltage circuit breaker equipment based on the comprehensive health evaluation model; an equipment failure prediction model is constructed, and the comprehensive equipment health score is input into the equipment failure prediction model to generate an equipment failure prediction result; the equipment operation data is obtained, and the comprehensive equipment maintenance score is determined based on the equipment maintenance evaluation model in combination with the equipment failure prediction result, and the corresponding equipment maintenance suggestion is generated according to the comprehensive equipment maintenance score; the comprehensive equipment health score, the equipment failure prediction result and the equipment maintenance suggestion are sent to the user interactive display interface, so that the operation status of the high-voltage circuit breaker equipment can be monitored in real time, the equipment failure can be discovered in time, the safe operation of the equipment can be ensured, and the management level and operation efficiency of the power equipment can be effectively improved.

[0017] The present invention collects and analyzes the operating data of high-voltage circuit breaker equipment in real time, combines big data and artificial intelligence technology, and can realize comprehensive monitoring and prediction of the health status of equipment, discover potential faults in advance, optimize equipment maintenance strategies, and extend the service life of equipment; through the system of the present invention, the operating status, fault anomalies, service life and maintenance status of high-voltage circuit breaker equipment can be grasped in time, the healthy operation of electrical equipment can be ensured, and the long-term trouble-free operation of high-voltage equipment can be ensured, thereby effectively improving the management level and operation efficiency of power equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A system block diagram of the health management prediction system based on the entire life cycle of electric high-voltage circuit breaker equipment of the present invention; Figure 2 This is a structural block diagram of the data acquisition and preprocessing module of the health management prediction system based on the entire life cycle of electric high-voltage circuit breaker equipment of the present invention. DETAILED DESCRIPTION

[0019] The present invention will be further described below in conjunction with the accompanying drawings and implementation modes.

[0020] like Figure 1 As shown, a health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment includes: The data acquisition and preprocessing module is used to acquire the original single-dimensional index data of the power high-voltage circuit breaker equipment in real time, and preprocess the original single-dimensional index data to generate target single-dimensional index data; A comprehensive health score calculation module, used to calculate the single-dimensional health index score corresponding to the target single-dimensional index data based on the single-dimensional index evaluation model, calculate the independent equipment health score of the electric high-voltage circuit breaker equipment according to the single-dimensional health index score based on the multi-dimensional health evaluation model, and calculate the comprehensive equipment health score according to the independent equipment health scores of all the electric high-voltage circuit breaker equipment based on the comprehensive health evaluation model; An equipment failure prediction module is used to construct an equipment failure prediction model and input the comprehensive equipment health score into the equipment failure prediction model to generate an equipment failure prediction result; An equipment maintenance suggestion generation module is used to obtain equipment operation data, combine the equipment failure prediction results, determine a comprehensive equipment maintenance score based on an equipment maintenance evaluation model, and generate corresponding equipment maintenance suggestions according to the comprehensive equipment maintenance score; The result sending and display module is used to send the comprehensive equipment health score, the equipment failure prediction result and the equipment maintenance suggestion to the user interaction display interface.

[0021] Among them, the data acquisition and preprocessing module can collect the original single-dimensional indicator data of the power high-voltage circuit breaker equipment in real time, including key parameters such as operating time, number of openings, number of closings, number of energy storage, etc., and generate standardized target single-dimensional indicator data through preprocessing operations such as data cleaning and normalization to ensure the accuracy and consistency of the data.

[0022] The comprehensive health score calculation module can first calculate the target single-dimensional indicator data based on the single-dimensional indicator evaluation model to generate single-dimensional health indicator scores such as operating life, opening life, closing life, and energy storage life. Then, the multi-dimensional health assessment model can be used to combine the single-dimensional health indicator scores to calculate the independent equipment health score of each power high-voltage circuit breaker device. Finally, based on the comprehensive health assessment model, the independent health scores of all devices can be weighted to generate a comprehensive equipment health score that fully reflects the overall health status of the equipment group.

[0023] The equipment failure prediction module can use the equipment failure prediction model, take the comprehensive equipment health score as input, combine it with historical failure data, and use machine learning algorithms to predict the type and time of possible future equipment failures to generate equipment failure prediction results.

[0024] The equipment maintenance recommendation generation module can calculate the comprehensive equipment maintenance score based on equipment operation data and fault prediction results through the equipment maintenance evaluation model, and generate targeted equipment maintenance recommendations based on the score, including maintenance time, maintenance content and priority, to help users optimize maintenance strategies.

[0025] Finally, the result sending and display module can send the comprehensive equipment health score, equipment fault prediction results and equipment maintenance suggestions to the user interactive display interface, presenting them in an intuitive and visual way, making it easier for equipment managers to understand the equipment status in real time and make decisions.

[0026] The health management prediction system can realize intelligent health management of power high-voltage circuit breaker equipment throughout its life cycle through the collaborative work of multiple modules, effectively improving the reliability and safety of power equipment operation.

[0027] like Figure 2 As shown, the data acquisition and preprocessing module 200 is used to collect the original single-dimensional index data of the power high-voltage circuit breaker equipment in real time, and preprocess the original single-dimensional index data to generate target single-dimensional index data, specifically including: The data acquisition unit 201 is used to collect the original single-dimensional indicator data in real time through the sensor network on the power high-voltage circuit breaker device, and the original single-dimensional indicator data includes the original operating time, the original opening number, the original closing number and the original energy storage number; A data cleaning unit 202 is used to clean the original single-dimensional index data, remove noise data, abnormal data and duplicate data in the original single-dimensional index data, and generate corresponding intermediate single-dimensional index data; The data normalization unit 203 is used to perform normalization processing on the intermediate single-dimensional indicator data to generate the corresponding target single-dimensional indicator data.

[0028] It is understandable that the data acquisition unit can collect the original single-dimensional indicator data of the equipment in real time through the distributed sensor network deployed on the power high-voltage circuit breaker equipment, including the original operating time of the equipment, the original number of openings, the original number of closings, the original number of energy storage, and other key operating parameters. The sensor network can ensure the real-time and integrity of the data through high-precision data acquisition technology, and provide reliable input for subsequent data processing and analysis.

[0029] The data cleaning unit can clean the collected original single-dimensional indicator data to eliminate noise, outliers and redundant information in the data. The unit uses a cleaning algorithm based on statistics and rule engines to identify and remove abnormal data points that do not conform to the normal operation logic of the equipment, while removing duplicate data records and generating intermediate single-dimensional indicator data, which significantly improves data quality.

[0030] The data normalization unit can normalize the cleaned intermediate single-dimensional indicator data to eliminate the dimensional differences between different data dimensions and ensure that the data is analyzed at the same scale for subsequent analysis. Normalization uses linear transformation or standardization methods to map the data to a unified numerical range to generate target single-dimensional indicator data. It should be noted that the normalized data is not only convenient for the training and prediction of machine learning models, but also can effectively improve the convergence speed and prediction accuracy of the algorithm.

[0031] Through the collaborative work of various units, the data acquisition and preprocessing module can efficiently complete the entire process from raw data acquisition to high-quality target data generation, providing reliable data support for the health management of power high-voltage circuit breaker equipment.

[0032] The calculating the single-dimensional health indicator score corresponding to the target single-dimensional indicator data based on the single-dimensional indicator evaluation model specifically includes: The target single-dimensional indicator data includes target operating time, target opening times, target closing times and target energy storage times; Obtaining the operating time parameter, the number of openings parameter, the number of closings parameter, the number of energy storage parameters and the number of historical faults of the electric high-voltage circuit breaker equipment, wherein the operating time parameter includes the historical operating time and the preset operating life time; the number of openings parameter includes the historical number of openings and the preset number of opening lifespans; the number of closings parameter includes the historical number of closings and the preset number of closing lifespans; the energy storage number parameter includes the historical number of energy storages and the preset number of energy storage lifespans; Based on the single-dimensional indicator evaluation model, the operating life score of the power high-voltage circuit breaker equipment is calculated according to the target operating time, the number of historical failures, the historical operating time and the preset operating life time. The corresponding calculation formula is as follows: In the formula, represents the operating life fraction; Indicates the weight corresponding to the operating life score; Indicates the target runtime; Indicates the preset operating life; represents the operational failure fraction; Indicates the weight corresponding to the operation fault score; Indicates the historical running time; Indicates the number of historical faults; The operation score that represents the correlation between the historical operation time and the historical failure number; represents the runtime life fraction; According to the target number of openings, the number of historical faults, the number of historical openings and the preset number of opening lifespans, the opening number lifespan score of the power high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, Indicates the breaking life fraction; Indicates the weight corresponding to the trip life score; Indicates the target number of trips; Indicates the preset number of opening life times; Indicates the breaking fault fraction; Indicates the weight corresponding to the trip fault score; Indicates the number of historical opening times; Indicates the number of historical faults; Indicates the correlation between the historical tripping times and the historical fault times; Indicates the life fraction of the number of trips; According to the target closing times, the historical fault times, the historical closing times and the preset closing life times, the closing times life score of the electric high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, Indicates the closing life fraction; Indicates the weight corresponding to the closing life score; Indicates the target closing times; Indicates the preset closing life times; Indicates the closing fault fraction; Indicates the weight corresponding to the closing fault score; Indicates the historical closing times; Indicates the number of historical faults; The closing score that represents the historical closing times and the historical fault times; Indicates the life fraction of the number of closing times; According to the target energy storage times, the historical fault times, the historical energy storage times and the preset energy storage life times, the energy storage times life score of the electric high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, represents the energy storage life fraction; Indicates the weight corresponding to the energy storage life score; Indicates the target energy storage times; Indicates the preset energy storage life times; represents the energy storage fault fraction; represents the weight corresponding to the energy storage fault score; Indicates the historical energy storage times; Indicates the number of historical faults; The energy storage score representing the correlation between the historical energy storage times and the historical fault times; Indicates the energy storage times life fraction; The single-dimensional health indicator score is obtained by summarizing the operating time life score, the opening times life score, the closing times life score and the energy storage times life score.

[0033] It is understandable that the target single-dimensional indicator data specifically includes the target operating time, target opening times, target closing times and target energy storage times. The relevant operating parameters of the power high-voltage circuit breaker equipment specifically include operating time parameters, opening times parameters, closing times parameters, energy storage times parameters and historical fault times. Among them, the operating time parameter is composed of the historical operating time and the preset operating life time; the opening times parameter is composed of the historical opening times and the preset opening life times; the closing times parameter is composed of the historical closing times and the preset closing life times; the energy storage times parameter is composed of the historical energy storage times and the preset energy storage life times.

[0034] First, based on the single-dimensional indicator evaluation model, the operating life score of the power high-voltage circuit breaker equipment can be calculated according to the target operating time, the number of historical failures, the historical operating time and the preset operating life. The score consists of two parts: the operating life score and the operating failure score. The operating life score is calculated by the ratio of the target operating time to the preset operating life, and the operating failure score is calculated by the associated operating score of the historical operating time and the number of historical failures. The two scores are multiplied by the corresponding weights and added together to obtain the operating life score.

[0035] Secondly, the opening times life score of the power high-voltage circuit breaker equipment can be calculated based on the target opening times, the historical fault times, the historical opening times and the preset opening life times. The score consists of two parts: the opening life score and the opening fault score. The opening life score is calculated by the ratio of the target opening times to the preset opening life times, and the opening fault score is calculated by the related opening scores of the historical opening times and the historical fault times. The two parts of the score are multiplied by the corresponding weights and added together to obtain the opening times life score.

[0036] Thirdly, the closing times life score of the power high-voltage circuit breaker equipment can be calculated based on the target closing times, the historical fault times, the historical closing times and the preset closing life times. The score consists of two parts: the closing life score and the closing fault score. The closing life score is calculated by the ratio of the target closing times to the preset closing life times, and the closing fault score is calculated by the related closing scores of the historical closing times and the historical fault times. The two parts of the score are multiplied by the corresponding weights and added together to obtain the closing times life score.

[0037] Finally, the energy storage times and life scores of the power high-voltage circuit breaker equipment can be calculated based on the target energy storage times, the historical failure times, the historical energy storage times, and the preset energy storage life times. The score consists of two parts: the energy storage life score and the energy storage failure score. The energy storage life score is calculated by the ratio of the target energy storage times to the preset energy storage life times, and the energy storage failure score is calculated by the associated energy storage scores of the historical energy storage times and the historical failure times. The two scores are multiplied by the corresponding weights and added together to obtain the energy storage times and life scores.

[0038] In practical applications, the operating time life score, the opening times life score, the closing times life score and the energy storage times life score can be summarized to obtain a single-dimensional health index score. This score can fully reflect the health status of the power high-voltage circuit breaker equipment in terms of single-dimensional indicators such as operating time, opening times, closing times and energy storage times.

[0039] Based on the multi-dimensional health assessment model, the independent device health score of the power high-voltage circuit breaker device is calculated according to the single-dimensional health indicator score, and the corresponding calculation formula is as follows: In the formula, Indicates the health score of an individual device; represents the runtime life fraction; Indicates the life fraction of the number of trips; Indicates the life fraction of the number of closing times; Indicates the energy storage times life fraction; Indicates the weight corresponding to the runtime life fraction; Indicates the weight corresponding to the life score of the number of trips; Indicates the weight corresponding to the life score of the number of closing times; Indicates the weight corresponding to the energy storage times life score.

[0040] It should be noted that the independent equipment health score of the power high-voltage circuit breaker equipment can be calculated based on the multi-dimensional health assessment model according to the single-dimensional health indicator score.

[0041] Specifically, the health score of an independent device is obtained by weighted summing the scores of four dimensions: operating longevity score, opening times life score, closing times life score, and energy storage times life score. Among them, the operating longevity score reflects the cumulative effect of the equipment's operating time, the opening times life score and closing times life score represent the cumulative losses of the equipment's opening and closing operations, respectively, and the energy storage times life score reflects the cumulative impact of the equipment's energy storage operations.

[0042] Each dimension score is multiplied by the corresponding weight coefficient and then added together to finally obtain the independent device health score. The sum of the weights of the scores of each dimension is 1 to ensure that the proportion of the scores of each dimension in the total score is reasonably distributed, so that the health status of the device can be comprehensively and quantitatively evaluated.

[0043] The comprehensive equipment health score is calculated based on the comprehensive health assessment model according to the independent equipment health scores of all the electric high-voltage circuit breaker equipment, and the corresponding calculation formula is as follows: In the formula, Indicates the overall device health score; Indicates the total number of power high voltage circuit breaker equipment; represents the independent equipment health score of the mth power high voltage circuit breaker equipment; Represents the weight corresponding to the independent device health score of the mth power high-voltage circuit breaker device.

[0044] In practical applications, the comprehensive equipment health score can be calculated based on the comprehensive health assessment model according to the independent equipment health scores of all power high-voltage circuit breaker equipment.

[0045] The calculation process adopts the weighted average method, that is, the comprehensive equipment health score is equal to the sum of the products of the independent equipment health scores of each device and its corresponding weight. Among them, the comprehensive equipment health score reflects the health status of the overall equipment, the total number of equipment represents the number of all high-voltage circuit breaker equipment in the system, and the independent equipment health score represents the health assessment result of a single device. The weight is dynamically adjusted according to the importance and operating status of the equipment in the system, so that the overall health level of the power high-voltage circuit breaker equipment can be comprehensively and accurately evaluated.

[0046] The equipment failure prediction module is used to construct an equipment failure prediction model and input the comprehensive equipment health score into the equipment failure prediction model to generate an equipment failure prediction result, specifically including: The comprehensive equipment health score is input into the equipment failure prediction model. The calculation formula of the forget gate of the equipment failure prediction model is as follows: In the formula, Represents the output of the forget gate at the current time t; Represents the weight corresponding to the forget gate; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of Represents the bias item corresponding to the forget gate; Represents the activation function.

[0047] The calculation formula of the input gate of the equipment failure prediction model is as follows: In the formula, Represents the output of the input gate at the current time t; Represents the candidate memory unit at the current time t; and Represent the weights corresponding to the input gate and the candidate memory unit respectively; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of and Represent the bias items corresponding to the input gate and the candidate memory unit respectively; represents the activation function; represents the hyperbolic tangent function.

[0048] The calculation formula for updating the memory unit of the equipment failure prediction model is as follows: In the formula, Represents the memory unit at the current time t; Represents the output of the forget gate at the current time t; Represents the memory unit at the previous time t-1; Represents the output of the input gate at the current time t; Represents the candidate memory unit at the current time t.

[0049] The calculation formula of the output gate of the equipment failure prediction model is as follows: In the formula, represents the output of the output gate at the current time t; represents the activation function; Represents the weight corresponding to the output gate; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of Represents the bias term corresponding to the output gate; represents the hidden state at the current time t; represents the hyperbolic tangent function; Represents the memory unit at the current time t; The output of the output gate of the equipment failure prediction model is the equipment failure prediction result.

[0050] It can be understood that the equipment failure prediction module can input the comprehensive equipment health score into the equipment failure prediction model, and based on the long short-term memory network (LSTM) architecture, it can achieve accurate prediction of equipment failure through multiple gating mechanisms.

[0051] Among them, the forget gate is used to control the degree of retention of the memory unit information at the previous moment. Its output is determined by the hidden state at the previous moment, the comprehensive equipment health score input at the current moment, and the corresponding weights and bias terms, and is transformed nonlinearly through the activation function. The input gate is used to adjust the impact of the current moment input information on the memory unit. Its output is combined with the calculation results of the candidate memory unit to further update the memory unit state at the current moment. The update process of the memory unit comprehensively considers the output of the forget gate and the input gate to ensure that the model can dynamically adjust the weight of historical information and current input information. Finally, the output gate generates the equipment fault prediction result based on the memory unit state and hidden state at the current moment. The result is normalized by the hyperbolic tangent function to ensure the rationality and interpretability of the output value.

[0052] Through the above steps, the equipment failure prediction module can effectively utilize the comprehensive equipment health score, combine historical data and current status, and achieve accurate prediction of future equipment failure types and occurrence times.

[0053] Each fault type in the equipment fault prediction result corresponds to a different preset fault code.

[0054] In actual applications, each fault type in the equipment fault prediction results corresponds to a different preset fault code, which is a unique identifier pre-set based on the equipment operating characteristics and historical fault data. Through the standardized coding of fault codes, the system can accurately classify and quickly identify various types of faults that may occur during equipment operation.

[0055] It can be understood that the preset fault codes not only facilitate the system to automatically count and analyze the fault types, but also provide equipment maintenance personnel with a clear basis for fault diagnosis, thereby effectively improving the efficiency and accuracy of fault handling.

[0056] In addition, the setting of fault codes also takes into account the equipment's operating environment, operating conditions and the probability distribution of fault occurrence, ensuring that each fault type can be accurately mapped to the corresponding fault code, providing reliable data support for equipment health management and predictive maintenance.

[0057] Through the introduction of the above embodiments, the present invention adopts a health management prediction system based on the whole life cycle of electric high-voltage circuit breaker equipment, including a data acquisition and preprocessing module, a comprehensive health score calculation module, an equipment failure prediction module, an equipment maintenance suggestion generation module and a result sending and display module. The original single-dimensional indicator data of the electric high-voltage circuit breaker equipment is collected in real time, and the original single-dimensional indicator data is preprocessed to generate target single-dimensional indicator data; the single-dimensional health indicator score corresponding to the target single-dimensional indicator data is calculated based on the single-dimensional indicator evaluation model, and the independent equipment health score of the electric high-voltage circuit breaker equipment is calculated according to the single-dimensional health indicator score based on the multi-dimensional health evaluation model; The model calculates the comprehensive equipment health score based on the independent equipment health scores of all power high-voltage circuit breaker equipment; constructs an equipment failure prediction model, and inputs the comprehensive equipment health score into the equipment failure prediction model to generate equipment failure prediction results; obtains equipment operation data, combines the equipment failure prediction results, determines the comprehensive equipment maintenance score based on the equipment maintenance evaluation model, and generates corresponding equipment maintenance suggestions based on the comprehensive equipment maintenance score; sends the comprehensive equipment health score, equipment failure prediction results and equipment maintenance suggestions to the user interactive display interface, so that the operating status of high-voltage circuit breaker equipment can be monitored in real time, equipment failures can be discovered in time, and safe operation of equipment can be ensured, effectively improving the management level and operating efficiency of power equipment.

[0058] The present invention collects and analyzes the operating data of high-voltage circuit breaker equipment in real time, combines big data and artificial intelligence technology, and can realize comprehensive monitoring and prediction of the health status of equipment, discover potential faults in advance, optimize equipment maintenance strategies, and extend the service life of equipment; through the system of the present invention, the operating status, fault anomalies, service life and maintenance status of high-voltage circuit breaker equipment can be grasped in time, the healthy operation of electrical equipment can be ensured, and the long-term trouble-free operation of high-voltage equipment can be ensured, thereby effectively improving the management level and operation efficiency of power equipment.

[0059] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0060] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0061] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A health management prediction system based on the entire life cycle of power high-voltage circuit breaker equipment, characterized in that: The prediction system comprises: The data acquisition and preprocessing module is used to acquire the original single-dimensional index data of the power high-voltage circuit breaker equipment in real time, and preprocess the original single-dimensional index data to generate target single-dimensional index data; A comprehensive health score calculation module, used to calculate the single-dimensional health index score corresponding to the target single-dimensional index data based on the single-dimensional index evaluation model, calculate the independent equipment health score of the electric high-voltage circuit breaker equipment according to the single-dimensional health index score based on the multi-dimensional health evaluation model, and calculate the comprehensive equipment health score according to the independent equipment health scores of all the electric high-voltage circuit breaker equipment based on the comprehensive health evaluation model; An equipment failure prediction module is used to construct an equipment failure prediction model and input the comprehensive equipment health score into the equipment failure prediction model to generate an equipment failure prediction result; An equipment maintenance suggestion generation module is used to obtain equipment operation data, combine the equipment failure prediction results, determine a comprehensive equipment maintenance score based on an equipment maintenance evaluation model, and generate corresponding equipment maintenance suggestions according to the comprehensive equipment maintenance score; The result sending and display module is used to send the comprehensive equipment health score, the equipment failure prediction result and the equipment maintenance suggestion to the user interactive display interface.

2. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 1 is characterized in that: The data acquisition and preprocessing module is used to collect the original single-dimensional index data of the power high-voltage circuit breaker equipment in real time, and preprocess the original single-dimensional index data to generate target single-dimensional index data, specifically including: A data acquisition unit, used to collect the original single-dimensional indicator data in real time through a sensor network on the power high-voltage circuit breaker device, and the original single-dimensional indicator data includes original operating time, original opening times, original closing times and original energy storage times; A data cleaning unit, used to clean the original single-dimensional indicator data, remove noise data, abnormal data and duplicate data in the original single-dimensional indicator data, and generate corresponding intermediate single-dimensional indicator data; The data normalization unit is used to perform normalization processing on the intermediate single-dimensional indicator data to generate the corresponding target single-dimensional indicator data.

3. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 1 is characterized in that: The calculating the single-dimensional health indicator score corresponding to the target single-dimensional indicator data based on the single-dimensional indicator evaluation model specifically includes: The target single-dimensional indicator data includes target operating time, target opening times, target closing times and target energy storage times; Obtaining the operating time parameter, the number of openings parameter, the number of closings parameter, the number of energy storage parameters and the number of historical faults of the electric high-voltage circuit breaker equipment, wherein the operating time parameter includes the historical operating time and the preset operating life time; the number of openings parameter includes the historical number of openings and the preset number of opening lifespans; the number of closings parameter includes the historical number of closings and the preset number of closing lifespans; the energy storage number parameter includes the historical number of energy storages and the preset number of energy storage lifespans; Based on the single-dimensional indicator evaluation model, the operating life score of the power high-voltage circuit breaker equipment is calculated according to the target operating time, the number of historical failures, the historical operating time and the preset operating life time. The corresponding calculation formula is as follows: In the formula, represents the operating life fraction; Indicates the weight corresponding to the operating life score; Indicates the target runtime; Indicates the preset operating life time; represents the operational failure fraction; Indicates the weight corresponding to the operation fault score; Indicates the historical running time; Indicates the number of historical faults; The operation score that represents the correlation between the historical operation time and the historical failure number; represents the runtime life fraction; According to the target number of openings, the number of historical faults, the number of historical openings and the preset number of opening lifespans, the opening number lifespan score of the power high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, Indicates the breaking life fraction; Indicates the weight corresponding to the trip life score; Indicates the target number of trips; Indicates the preset number of opening life times; Indicates the breaking fault fraction; Indicates the weight corresponding to the trip fault score; Indicates the number of historical trips; Indicates the number of historical faults; Indicates the correlation between the historical tripping times and the historical fault times; Indicates the life fraction of the number of trips; According to the target closing times, the historical fault times, the historical closing times and the preset closing life times, the closing times life score of the electric high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, Indicates the closing life fraction; Indicates the weight corresponding to the closing life score; Indicates the target closing times; Indicates the preset closing life times; Indicates the closing fault fraction; Indicates the weight corresponding to the closing fault score; Indicates the historical closing times; Indicates the number of historical faults; The closing score represents the correlation between the number of historical closings and the number of historical faults; Indicates the life fraction of the number of closing times; According to the target energy storage times, the historical fault times, the historical energy storage times and the preset energy storage life times, the energy storage times life score of the electric high-voltage circuit breaker equipment is calculated, and the corresponding calculation formula is as follows: In the formula, represents the energy storage life fraction; Indicates the weight corresponding to the energy storage life score; Indicates the target energy storage times; Indicates the preset energy storage life times; represents the energy storage fault fraction; represents the weight corresponding to the energy storage fault score; Indicates the historical energy storage times; Indicates the number of historical faults; The energy storage score representing the correlation between the historical energy storage times and the historical fault times; Indicates the energy storage times life fraction; The single-dimensional health indicator score is obtained by summarizing the operating time life score, the opening times life score, the closing times life score and the energy storage times life score.

4. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 3 is characterized in that: Based on the multi-dimensional health assessment model, the independent device health score of the power high-voltage circuit breaker device is calculated according to the single-dimensional health indicator score, and the corresponding calculation formula is as follows: In the formula, Indicates the health score of an individual device; represents the runtime life fraction; Indicates the life fraction of the number of trips; Indicates the life fraction of the number of closing times; Indicates the energy storage times life fraction; Indicates the weight corresponding to the runtime life fraction; Indicates the weight corresponding to the life score of the number of trips; Indicates the weight corresponding to the life score of the number of closing times; Indicates the weight corresponding to the energy storage times life score.

5. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 4 is characterized in that: The comprehensive equipment health score is calculated based on the comprehensive health assessment model according to the independent equipment health scores of all the electric high-voltage circuit breaker equipment, and the corresponding calculation formula is as follows: In the formula, Indicates the overall device health score; Indicates the total number of power high voltage circuit breaker equipment; represents the independent equipment health score of the mth power high voltage circuit breaker equipment; Represents the weight corresponding to the independent device health score of the mth power high-voltage circuit breaker device.

6. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 1 is characterized in that: The equipment failure prediction module is used to construct an equipment failure prediction model and input the comprehensive equipment health score into the equipment failure prediction model to generate an equipment failure prediction result, specifically including: The comprehensive equipment health score is input into the equipment failure prediction model. The calculation formula of the forget gate of the equipment failure prediction model is as follows: In the formula, Represents the output of the forget gate at the current time t; Represents the weight corresponding to the forget gate; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of Represents the bias item corresponding to the forget gate; Represents the activation function.

7. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 6 is characterized in that: The calculation formula of the input gate of the equipment failure prediction model is as follows: In the formula, Represents the output of the input gate at the current time t; Represents the candidate memory unit at the current time t; and Represent the weights corresponding to the input gate and the candidate memory unit respectively; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of and Represent the bias items corresponding to the input gate and the candidate memory unit respectively; represents the activation function; represents the hyperbolic tangent function.

8. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 7 is characterized in that: The calculation formula for updating the memory unit of the equipment failure prediction model is as follows: In the formula, Represents the memory unit at the current time t; Represents the output of the forget gate at the current time t; Represents the memory unit at the previous time t-1; Represents the output of the input gate at the current time t; Represents the candidate memory unit at the current time t.

9. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 8 is characterized in that: The calculation formula of the output gate of the equipment failure prediction model is as follows: In the formula, represents the output of the output gate at the current time t; represents the activation function; Represents the weight corresponding to the output gate; Represents the hidden state at the previous moment t-1; Represents the comprehensive device health score input at the current time t; Indicates hidden state and overall device health score The vector composed of Represents the bias term corresponding to the output gate; represents the hidden state at the current time t; represents the hyperbolic tangent function; Represents the memory unit at the current time t; The output of the output gate of the equipment failure prediction model is the equipment failure prediction result.

10. The health management prediction system based on the full life cycle of electric high-voltage circuit breaker equipment according to claim 9 is characterized in that: Each fault type in the equipment fault prediction result corresponds to a different preset fault code.

Images