Method and system for predicting effective remaining electrical life of high-voltage circuit breaker

Abstract

A method and system for predicting an effective remaining electrical life of a high-voltage circuit breaker. A circuit breaker electrical life test is carried out and associated data sets of single arcing times and single arcing energy are constructed; a degree of wear of a contact is replaced with accumulated arcing energy to characterize whether a circuit breaker fails; and function fitting is used to construct the relationship between the single arcing energy and the single arcing times; and on this basis, the method for predicting an effective remaining electrical life of a high-voltage circuit breaker is formed. Therefore, the rapid and accurate prediction of a remaining service life of a circuit breaker can be realized only by measuring simple data, thereby providing guarantee for the reliable operation of a power grid.

Description

Method and system for predicting effective residual electrical life of high-voltage circuit breaker

[0001] The present application claims priority from the Chinese patent application No. 202410520967.6 filed on April 28, 2024, and entitled "Method and system for predicting effective residual electrical life of high-voltage circuit breaker", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the technical field of high-voltage power transmission and protection equipment, and particularly relates to a method and system for predicting effective residual electrical life of high-voltage circuit breaker. BACKGROUND

[0003] Circuit breakers are common switching devices in power systems, which can turn on or turn off normal load current and overload current. With the large number of load access and the increasingly complex grid structure, higher requirements are put forward for the reliability and service life of circuit breakers. With the increase of operation times, the accumulation of wear and tear and aging of circuit breakers will lead to the decline of their service life and reliability. The main indicators reflecting the reliability are mechanical life and electrical life. The mechanical life of circuit breakers is always designed to be much higher than the electrical life, so most of the discussions on the life prediction of circuit breakers refer to the electrical life. When the circuit breaker switches the current, material spatter and transfer will occur between the contacts accompanied by arc, which will cause wear and loss of the contact material, which is the main reason for the reduction of electrical life. The decline of circuit breaker reliability will bring great threat and risk to the safe operation of the power grid. If the fault cannot be removed, it is extremely likely to cause damage to important equipment, and even cause a fire. Real-time monitoring of the state of the circuit breaker and accurate prediction of its residual effective life can guide the staff to carry out timely maintenance and replacement of the circuit breaker, and ensure the reliable operation of the power system.

[0004] In practical applications, the reliability of circuit breakers is often ensured by periodic replacement. This method uses time as a measure to replace circuit breakers that exceed the safe use period. However, due to different operating frequencies and breaking current sizes in different situations, some circuit breakers with less breaking times and small connected loads still have a lot of remaining life within the safe period. At this time, replacement will cause waste of resources. Relying on cumulative number to judge the remaining life of circuit breakers is also a common life prediction method. However, the loss of a single operation to the contact has a close relationship with the arc time and current size, and has great uncertainty. Relying on cumulative number to judge the remaining life has low reliability, and may cause waste of resources by replacing the equipment in good operating condition in advance, or may fail to find seriously deteriorated equipment in time to bring safety hazards to the power system. At present, there are also studies on predicting circuit breakers by relying on vibration signals combined with artificial intelligence algorithms, but complex sensor systems need to be installed, which increases the cost and is easily disturbed by the environment. Therefore, a technology is needed to realize real-time life prediction of circuit breakers.

[0005] SUMMARY

[0006] The application provides an effective residual electric life prediction method and system for a high-voltage circuit breaker, which solves the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker, thereby bringing safety hazards to the power system.

[0007] The first aspect of the application provides an effective residual electric life prediction method for a high-voltage circuit breaker, comprising:

[0008] In response to a life test request for a test circuit breaker, a test operation data set associated with the test circuit breaker is acquired in real time;

[0009] The test operation data set is input into a preset single-arc function to generate a single-arc time data set and a single-arc energy data set;

[0010] The single-arc energy data set is input into a preset total circuit breaker arc energy function to generate a total circuit breaker arc energy;

[0011] The single-arc time data set and the single-arc energy data set are functionally fitted, and a target circuit breaker electric life prediction model is constructed in combination with the total circuit breaker arc energy;

[0012] The life of a circuit breaker to be predicted is predicted by the target circuit breaker electric life prediction model to generate a life prediction result.

[0013] Optionally, the test operation data set includes arc voltage data between the contacts of the circuit breaker during the operation process, arc current data between the contacts, arc start time data, and arc extinguishing time data;

[0014] The arc initiation time data and the arc extinction time data are determined by mechanical factor measurement method or transient current method.

[0015] Optionally, the preset single-arc burning function includes a single-arc burning time function and a single-arc burning energy function. The step of using the test run dataset as input to the preset single-arc burning function to generate a single-arc burning time dataset and a single-arc burning energy dataset includes:

[0016] The single arcing time dataset is generated by inputting the arc initiation time data and the arc extinction time data into the single arcing time function.

[0017] The specific single-attack arcing time function is as follows:

[0018] t arci =t 2i -t 1i

[0019] In the formula, t arci Let t represent the single arc-ignition time data for the i-th time, where i = 1, 2, ..., n, and n represents the number of times the switching action is completed. The single arc-ignition time dataset consists of n such single arc-ignition time data points. 1i t represents the arc initiation time data during the i-th action. 2i This represents the time when the arc extinguishes during the i-th action;

[0020] The single arc energy dataset is generated by inputting the arc initiation time data, the arc extinction time data, the arc voltage data at both ends, and the arc current data between the contacts into the single arc energy function.

[0021] The specific energy function for a single arc burning event is as follows:

[0022] In the formula, ΔE arci This represents the energy data of the i-th single arc ignition, where the single arc ignition energy dataset consists of n such single arc ignition energy data points, U i (t) represents the arc voltage data at both ends at time t during the i-th action, I i (t) represents the arc current data between the contacts at time t during the i-th action, where t represents the sampling interval.

[0023] Optionally, the preset total arc energy function of the circuit breaker is specifically:

[0024] In the formula, E pe The value represents the total arc energy of the circuit breaker, and n represents the number of times the breaking action is completed.

[0025] Optionally, the step of performing function fitting on the single-arc time data set and the single-arc energy data set and constructing a target circuit breaker electrical life prediction model in combination with the total circuit breaker arc energy comprises:

[0026] obtaining basic parameters associated with the test circuit breaker and inputting the basic parameters into a preset circuit breaker reference prediction model platform for matching to obtain a reference prediction model;

[0027] performing function fitting on the reference prediction model based on a function fitting method, and constructing an initial circuit breaker electrical life prediction model in combination with the total circuit breaker arc energy and the single-arc time data set and the single-arc energy data set;

[0028] The function fitting relationship is specifically:

[0029] ΔE predi =f(t arci )

[0030] In the formula, ΔE predi represents the single-arc energy obtained by function fitting through a function fitting method, f(t arci ) represents a function relationship with the optimal fitting effect;

[0031] inputting a preset training operation data set into the initial circuit breaker electrical life prediction model for training to generate a training prediction life;

[0032] determining a standard prediction life by using the single-arc energy data set and the total circuit breaker arc energy;

[0033] determining an average prediction accuracy by using the training prediction life and the standard prediction life;

[0034] generating a target circuit breaker electrical life prediction model when the average prediction accuracy is greater than a preset standard prediction accuracy.

[0035] Optionally, a target function of the target circuit breaker electrical life prediction model is specifically:

[0036] In the formula, r predk represents a predicted remaining life at the kth action, represents a target cumulative arc energy obtained by fitting up to the ith action, and k represents a current breaking action number.

[0037] Optionally, the step of determining a standard prediction life by using the single-arc energy data set and the total circuit breaker arc energy comprises:

[0038] Input the single arc energy data set into a preset cumulative arc energy function to generate a cumulative arc energy set;

[0039] The preset cumulative arc energy function is specifically:

[0040] In the formula, E k represents the cumulative arc energy of the circuit breaker after the kth operation, the cumulative arc energy set has k cumulative arc energies, and k represents the number of kth breaking operations;

[0041] Input the cumulative arc energy set and the total arc energy of the circuit breaker into a preset standard predicted life function to determine the standard predicted life;

[0042] The preset standard predicted life function is specifically:

[0043] In the formula, r k represents the standard predicted life of the circuit breaker after the kth operation.

[0044] Optionally, the step of determining the average prediction accuracy by using the training predicted life and the standard predicted life comprises:

[0045] Input the training predicted life and the standard predicted life into a preset life prediction accuracy function to generate a life prediction accuracy set;

[0046] The preset life prediction accuracy function is specifically:

[0047] In the formula, a k represents the life prediction accuracy of the circuit breaker after the kth operation, and the life prediction accuracy set is composed of k life prediction accuracies;

[0048] Input the life prediction accuracy set into a preset average prediction accuracy function to determine the average prediction accuracy;

[0049] The preset average prediction accuracy function is specifically:

[0050] In the formula, a represents the average prediction accuracy, and a i represents the life prediction accuracy of the circuit breaker after the ith operation.

[0051] The second aspect of the present application provides an effective residual electrical life prediction system of a high-voltage circuit breaker, comprising:

[0052] A response module is configured to acquire a test running data set associated with a test circuit breaker in real time in response to a life test request of the test circuit breaker;

[0053] a single-arc operation module, configured to input a preset single-arc function with the test running data set to generate a single-arc time data set and a single-arc energy data set;

[0054] a total circuit breaker arc energy module, configured to input a preset total circuit breaker arc energy function with the single-arc energy data set to generate total circuit breaker arc energy;

[0055] a function fitting module, configured to perform function fitting on the single-arc time data set and the single-arc energy data set based on a function fitting method to generate a target circuit breaker electrical life prediction model;

[0056] a life prediction module, configured to perform life prediction on a circuit breaker to be predicted through the target circuit breaker electrical life prediction model to generate a life prediction result.

[0057] The third aspect of the present application provides an electronic device, comprising a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to make the processor execute the steps of the effective residual electrical life prediction method of the high-voltage circuit breaker according to any one of the above.

[0058] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed to implement the effective residual electrical life prediction method of the high-voltage circuit breaker according to any one of the above.

[0059] From the above technical solutions, the present application has the following advantages:

[0060] The present application responds to the life test request of the test circuit breaker, acquires the test running data set associated with the test circuit breaker in real time, inputs a preset single-arc function with the test running data set to generate a single-arc time data set and a single-arc energy data set, performs function fitting on the single-arc time data set and the single-arc energy data set based on a function fitting method to generate a target circuit breaker electrical life prediction model, performs life prediction on a circuit breaker to be predicted through the target circuit breaker electrical life prediction model to generate a life prediction result, and solves the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker, thereby bringing safety hazards to the power system.

[0061] 1) The present application comprehensively considers the relationship between cumulative arc energy and contact wear mass, and uses electrical signal parameters to represent contact mechanical parameters, which is simple and easy to implement.

[0062] 2) The present application establishes the relationship between arc time and arc energy during the breaking process of the circuit breaker, constructs a life prediction model, and the prediction result has high reliability and high accuracy.

[0063] 3) The feature extraction content of the present application is simple, the process is easy, the required sensor volume is small and easy to install, and the influence on the normal operation of the circuit breaker is small.

[0064] 4) The present application avoids massive data storage and calculation, can realize the effect of rapid prediction, and the requirement of data processor is simple.

[0065] 5) The present application can be integrated into the power transmission and transformation network operation and maintenance platform or digital signal processor for real-time monitoring of the operating state of the circuit breaker.

[0066] 6) The present application has certain portability and can be applied to different objects or different scenes for life prediction of the circuit breaker. BRIEF DESCRIPTION OF DRAWINGS

[0067] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the following embodiment or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0068] Fig. 1 is a step flow chart of a method for predicting the effective residual electrical life of a high-voltage circuit breaker according to an embodiment of the present application;

[0069] Fig. 2 is a step flow chart of a method for predicting the effective residual electrical life of a high-voltage circuit breaker according to an embodiment of the present application;

[0070] Fig. 3 is a schematic diagram of a fitting function of single arc energy and arc time according to an embodiment of the present application;

[0071] Fig. 4 is a schematic diagram of comparison between actual life and predicted life according to an embodiment of the present application;

[0072] Fig. 5 is a flow chart of a method for predicting the effective residual electrical life of a high-voltage circuit breaker according to an application example of the present application.

[0073] Fig. 6 is a structural block diagram of a system for predicting the effective residual electrical life of a high-voltage circuit breaker according to an embodiment of the present application.

[0074] Fig. 7 is a schematic diagram of a frame of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0075] The present application provides a method and system for predicting the effective residual electrical life of a high-voltage circuit breaker, which solves the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker, causing safety hazards to the power system.

[0076] In order to make the application purposes, features and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings of the embodiments of the present application. Obviously, the embodiments described below are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts fall within the scope of the present application.

[0077] The present application provides an effective residual electrical life prediction method and system for a high-voltage circuit breaker, which is mainly applied to the protection equipment of a high-voltage power distribution system.

[0078] Another object is to provide an effective residual electrical life prediction method for a high-voltage circuit breaker, which realizes accurate, reliable and fast circuit breaker life prediction and degradation evaluation, and provides protection for the safe operation of the high-voltage power distribution system.

[0079] Another object is to provide an effective residual electrical life prediction method for a high-voltage circuit breaker, which guides the maintenance and replacement of circuit breakers in the system, maximizes the utilization of circuit breakers, and timely repairs or replaces circuit breakers that exceed the safe service life, providing a reliable reference for maintenance work for workers.

[0080] Another object is to form a residual effective life prediction system for circuit breakers, which centrally monitors and manages the state of circuit breaker equipment in the region.

[0081] Please refer to FIG. 1, which is a step flowchart of an effective residual electrical life prediction method for a high-voltage circuit breaker provided by the first embodiment of the present application.

[0082] The effective residual electrical life prediction method for a high-voltage circuit breaker provided by the present application comprises:

[0083] Step 101, in response to a life test request for a test circuit breaker, real-time acquisition of a test operation data set associated with the test circuit breaker.

[0084] The life test request refers to a request information for testing the electrical life of the circuit breaker by using the test circuit breaker as a sample machine.

[0085] The test operation data set refers to real-time collection data of the arc voltage between the contacts, the arc current between the contacts, the arc ignition time and the arc extinguishing time during the operation process of the circuit breaker associated with the test circuit breaker, which is classified and integrated according to the collection time and data type, and forms a data set.

[0086] In the embodiment of the present application, in response to receiving the request information for testing the circuit breaker as a prototype, performing the circuit breaker electrical life experiment test, the real-time acquisition data set of the arc voltage between the contacts, the arc current between the contacts, the arc starting time and the arc extinguishing time of the circuit breaker action process associated with the test circuit breaker is obtained.

[0087] Step 102, input the preset single arc function with the test running data set to generate a single arc time data set and a single arc energy data set.

[0088] The preset single arc function refers to a single arc time function and a single arc energy function for calculating the single arc time and the single arc energy of the circuit breaker.

[0089] The single arc time data set refers to inputting the single arc time function with the test running data set to calculate a data set composed of multiple single arc times.

[0090] The single arc energy data set refers to inputting the single arc energy function with the test running data set to calculate a data set composed of multiple single arc energies.

[0091] In the embodiment of the present application, the preset single arc function is input with the test running data set to generate a single arc time data set composed of multiple single arc times and a single arc energy data set composed of multiple single arc energies.

[0092] Step 103, input the preset circuit breaker total arc energy function with the single arc energy data set to generate the circuit breaker total arc energy.

[0093] In the embodiment of the present application, the preset circuit breaker total arc energy function is input with the single arc energy data set to calculate the circuit breaker total arc energy.

[0094] Step 104, function fitting is performed on the single arc time data set and the single arc energy data set, and a target circuit breaker electrical life prediction model is constructed in combination with the circuit breaker total arc energy.

[0095] Function fitting refers to function fitting based on the calculated single arc time data set and the single arc energy data set to establish a function relationship between the arc time and the arc energy.

[0096] The target circuit breaker electrical life prediction model refers to continuously training the function relationship between the arc time and the arc energy established as the objective function of the model, and constructing the electrical life prediction model in combination with the circuit breaker total arc energy.

[0097] In the embodiment of the present application, a function fitting method is used to establish a functional relationship between the arc time and the arc energy, and a target circuit breaker electrical life prediction model is constructed in combination with the total arc energy of the circuit breaker.

[0098] Step 105, life prediction is performed on the to-be-predicted circuit breaker through the target circuit breaker electrical life prediction model to generate a life prediction result.

[0099] In the embodiment of the present application, when the to-be-predicted operation data of the to-be-predicted circuit breaker is received, the to-be-predicted operation data is input into the target circuit breaker electrical life prediction model for life prediction, and a life prediction result of the to-be-predicted circuit breaker is output.

[0100] In the embodiment of the present application, in response to a life test request for the test circuit breaker, a test operation data set associated with the test circuit breaker is acquired in real time, the test operation data set is input into a preset single-arc function to generate a single-arc time data set and a single-arc energy data set, a function fitting method is used to perform function fitting on the single-arc time data set and the single-arc energy data set to generate a target circuit breaker electrical life prediction model, life prediction is performed on the to-be-predicted circuit breaker through the target circuit breaker electrical life prediction model to generate a life prediction result; the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker and brings a safety hazard to the power system is solved; first, the relationship between the arc time and the arc energy in the breaking process of the circuit breaker is established, and the target circuit breaker electrical life prediction model is constructed, so that the prediction result has high reliability and high accuracy; second, the present application avoids massive data storage and calculation, can realize fast prediction, and has simple requirements for data processors; finally, the present application can be integrated into a power transmission and transformation network operation and maintenance platform or a digital signal processor, and the target circuit breaker electrical life prediction model is input through real-time acquisition of operation data, which is used for real-time monitoring of the operating state of the circuit breaker.

[0101] Please refer to FIG. 2, which is a step flowchart of a high-voltage circuit breaker effective residual electrical life prediction method provided in the second embodiment of the present application.

[0102] The present application provides a high-voltage circuit breaker effective residual electrical life prediction method, which comprises:

[0103] Step 201, in response to a life test request for the test circuit breaker, a test operation data set associated with the test circuit breaker is acquired in real time.

[0104] In the embodiment of the present application, the specific implementation process of step 201 is similar to that of step 101, and will not be described here.

[0105] Further, the test running data set includes arc voltage data between contacts, arc current data between contacts, arc starting time data and arc extinguishing time data during the breaker action process;

[0106] The arc starting time data and the arc extinguishing time data are determined by a mechanical factor determination method or a transient current method.

[0107] It should be noted that in order to obtain the test running data set between the single arc time and the single arc energy of the circuit breaker, the circuit breaker electrical life experiment test is performed, and the test running data set includes arc voltage data U between contacts, arc current data I between contacts, arc starting time data t1 and arc extinguishing time data t2 during the circuit breaker action process. i i The data can be collected by measuring instruments such as voltage probes, current probes (Rogowski coils), oscilloscopes, etc., or the values of the intelligent monitoring instrument of the branch where the circuit breaker is located can be read.

[0108] It should be noted that the single arc time is specifically defined. Assuming that the arc starting time is t1 and the arc extinguishing time is t2 in a certain tripping action of the circuit breaker, the single arc time t can be represented by the following formula:

[0109] t arc = t2-t1

[0110] During the breaking process of the circuit breaker, the tripping action needs to overcome the pressure of the moving and static contacts first, and there is a short pause time. However, since the time difference from receiving the tripping signal to the start of the arc is very small, it can be ignored compared to the entire arc time, and it can be considered that the circuit breaker receives the tripping instruction at the moment t1, and the arc extinguishing time t2 can be determined by monitoring the change of the moving contact acceleration through the sensor.

[0111] It is worth mentioning that the mechanical factor determination method refers to first taking the moment when the circuit breaker receives the tripping instruction as the arc starting time, secondly determining the arc extinguishing time by monitoring the change of the moving contact acceleration through the acceleration sensor, and finally determining the single arc time by calculating the difference between the arc starting time and the arc extinguishing time.

[0112] According to the mechanical factor, the arc time can be calculated, which is not the only method. The arc starting time data t1 and the arc extinguishing time data t2 can also be determined by the transient current method.

[0113] The transient current method refers to monitoring the current signal during the tripping of the circuit breaker, performing data fitting after low-pass filtering, predicting the current change in a short time, comparing with the actual current to obtain the breaking starting and ending points, and the difference between the two is the arc time.

[0114] ​It should be noted that the arc ignition time data and the arc extinguishing time data in the embodiment can be determined by a mechanical factor determination method or a transient current method, the data is obtained by two ways, the data source is more extensive, when the data is verified, the data obtained by two ways can be verified with each other, so that the prediction result is more accurate.

[0115] Further, the preset single-arc function includes a single-arc time function and a single-arc energy function.

[0116] Step 202, inputting the arc ignition time data and the arc extinguishing time data into the single-arc time function to generate a single-arc time data set;

[0117] The single-arc time function is specifically:

[0118] t arci = t 2i - t 1i

[0119] In the formula, t arci represents the i-th single-arc time data, wherein i=1, 2, …, n, n represents the number of times of completing the breaking action, the single-arc time data set is composed of n single-arc time data, t 1i represents the arc ignition time data at the i-th action, t 2i represents the arc extinguishing time data at the i-th action.

[0120] In the embodiment of the application, the arc ignition time data and the arc extinguishing time data are input into the single-arc time function to generate a single-arc time data set.

[0121] Step 203, inputting the arc ignition time data, the arc extinguishing time data, the two-end arc voltage data and the arc current data between the contacts into the single-arc energy function to generate a single-arc energy data set;

[0122] It is worth mentioning that the single-arc energy is specifically defined, and the single-arc energy (assuming the i-th) can be calculated by the following formula:

[0123] In the formula, ΔE arci is the arc energy of the i-th circuit breaker tripping, t 1i is the arc start time of the i-th action, t 2i is the arc end time, U i is the arc voltage, and I i is the arc current.

[0124] Since signal acquisition is a discrete time consumption, there is a sampling interval, and the single-arc energy is obtained from the following single-arc energy function in actual calculation.

[0125] The single-arc energy function is specifically:

[0126] In the formula, ΔE arci represents the i-th single-arc energy data, the single-arc energy data set is composed of n single-arc energy data, U i (t) represents the two-terminal arc voltage data at the i-th action t moment, I i (t) represents the arc current data between the contacts at the i-th action t moment, and t represents the sampling interval.

[0127] In the embodiment of the present application, the single-arc energy function is input with the arc starting time data, the arc extinguishing time data, the two-terminal arc voltage data and the arc current data between the contacts to generate the single-arc energy data set.

[0128] Step 204, input the single-arc energy data set into the preset circuit breaker total arc energy function to generate the circuit breaker total arc energy.

[0129] The preset circuit breaker total arc energy function is specifically:

[0130] In the formula, E pe represents the circuit breaker total arc energy, and n represents the number of completed breaking actions.

[0131] It should be noted that during the electrical life experiment, the wear condition of the circuit breaker contact is taken as the standard for judging the end of the life of the circuit breaker. Specifically, if the allowable wear thickness of the circuit breaker is a, when the life experiment is performed to the sample contact wear thickness greater than or equal to a, the circuit breaker is considered to be invalid, and it is assumed that n breaking operations have been completed, and the circuit breaker total arc energy is:

[0132] The obtained E pe is used as a new safety threshold to judge the degradation of the circuit breaker and whether the life ends.

[0133] It should be noted that the allowable wear thickness is replaced by the circuit breaker total arc energy E pe to explain the original explanation for judging the end of the life of the circuit breaker. When the circuit breaker breaks under load, an arc is generated between the contacts, accompanied by a large amount of light and heat, which is an energy transfer process. The generation of the arc is essentially a gas discharge phenomenon. When the contacts of the circuit breaker are broken, there is enough current and voltage between the contacts, the air between the contacts is broken down, and a self-sustaining discharge phenomenon occurs, and the current gas conducts electricity. In the process of generating the arc, the contact material will be worn, and the size of the wear is positively correlated with the energy of the arc, that is, the size of the current and voltage, so the quality loss of the contact can be quantified by the arc energy.

[0134] It is worth mentioning that the present application comprehensively considers the relationship between cumulative arc burning energy and contact wear mass, uses cumulative arc burning energy to replace contact wear degree to represent whether the circuit breaker is invalid, and uses electrical signal parameters to represent contact mechanical parameters, which is simple and easy to implement.

[0135] In the embodiment of the present application, the single arc burning energy data set is input into the preset circuit breaker total arc energy function for operation to generate the circuit breaker total arc energy.

[0136] In step 205, the single arc burning time data set and the single arc burning energy data set are functionally fitted, and an initial circuit breaker electrical life prediction model is constructed in combination with the circuit breaker total arc energy.

[0137] Further, step 205 can include the following sub-steps:

[0138] S11, obtain the basic parameters associated with the test circuit breaker, and input the basic parameters into the preset circuit breaker reference prediction model platform for matching to obtain the reference prediction model.

[0139] In the embodiment of the present application, the basic parameters of the test circuit breaker are input, the basic parameters include device parameters and electrical parameters, and the specific basic parameters include the rated working voltage, the rated working current, the rated short-circuit breaking current and the rated peak withstand current of the circuit breaker, and other parameters are selectively input according to the actual application of the circuit breaker.

[0140] It is worth mentioning that the preset circuit breaker reference prediction model platform refers to a reference prediction model associated with a plurality of prediction functions with different function parameter types and function parameters, each reference prediction model corresponds to a high-voltage circuit breaker with a certain basic parameter. When the user inputs the basic parameters of the high-voltage circuit breaker to be detected, the system automatically matches the reference prediction model associated with the corresponding prediction function. The input of the basic parameters here is to match the function fitting in the subsequent process. The model parameters of the circuit breakers with different parameters may be different, therefore, the input of the circuit breaker parameters can match the reference prediction model with appropriate model parameters, and better prediction accuracy can be achieved.

[0141] S12, based on the function fitting method, functionally fitting the single arc burning time data set and the single arc burning energy data set to the reference prediction model, and constructing an initial circuit breaker electrical life prediction model in combination with the circuit breaker total arc energy;

[0142] The function fitting relationship is specifically:

[0143] ΔE predi =f(t arci )

[0144] In the formula, ΔEpredi represents the single-arc energy obtained by function fitting through a function fitting method, f(t arci represents the function relationship with the optimal fitting effect.

[0145] The function fitting method refers to a polynomial, a Fourier function, a quadratic Gaussian function, and a Weibull distribution function.

[0146] In the embodiment of the present application, a function relationship between the arc time and the arc energy is established according to the calculated single-arc time data set and the single-arc energy data set, a function fitting function between the single-arc time and the single-arc energy is obtained by using a function fitting method, and the target function of the initial circuit breaker electrical life prediction model is constructed in combination with the total arc energy of the circuit breaker.

[0147] It is worth mentioning that ΔE predi represents the single-arc energy obtained by function fitting, the function relationship with the optimal fitting effect is selected as f, typically, f can be a polynomial, a Fourier function, a quadratic Gaussian function, and a Weibull distribution function, or can be obtained by an artificial intelligence algorithm fitting method.

[0148] It should be noted that the feasibility of constructing the function relationship between the single-arc energy and the single-arc time in the function fitting is explained. In the process of breaking the rated current, the contact separation time is approximately the arc generation time, the arc is extinguished at the current zero point, the arc current waveform is approximately the same as the load current waveform, but the arc voltage presents a nonlinear change. The arc time and the current and voltage waveform during the arc are closely related to the arc phase, when the arc phase is different, the arc current and voltage waveform also has obvious differences. The waveform of the arc voltage is related to the development of the arc, and the development of the arc in the breaking process of the circuit breaker has obvious stages, the arc voltage at each stage can be represented by a function, and has a certain rule. This rule is reflected in the single-arc energy, that is, the single-arc energy and the arc time (depending on the arc phase) have obvious nonlinear correlation.

[0149] S13, inputting a preset training running data set into the initial circuit breaker electrical life prediction model to perform training, and generating a training prediction life.

[0150] In the formula, r predk训 represents the training prediction life, t arci训 represents the fitting arc energy of the i th breaking, and is the training cumulative arc energy obtained by fitting up to the k th action.

[0151] In the embodiment of the present application, a preset training running data set is input into the initial circuit breaker electrical life prediction model to perform training, and a training prediction life is generated.

[0152] S14, determine the standard predicted life by using the single arc energy data set and the total arc energy of the circuit breaker.

[0153] Further, S14 can include the following sub-steps:

[0154] S141, input the preset cumulative arc energy function by using the single arc energy data set to generate a cumulative arc energy set;

[0155] The preset cumulative arc energy function is specifically:

[0156] In the formula, E k represents the cumulative arc energy of the circuit breaker after the kth action, the cumulative arc energy set has k cumulative arc energies, and k represents the number of kth breaking actions.

[0157] In the embodiment of the application, based on the obtained single arc energy data set, the correlation data set of the cumulative arc energy of the circuit breaker and the remaining effective electric life is obtained, and the correlation data set here refers to the cumulative arc energy set.

[0158] S142, input the preset standard predicted life function by using the cumulative arc energy set and the total arc energy of the circuit breaker to determine the standard predicted life;

[0159] It is worth mentioning that, in order to facilitate calculation and unified expression, the cumulative arc energy of the circuit breaker is normalized. Based on the obtained cumulative arc energy and the total arc energy of the circuit breaker, the total life of the circuit breaker is defined as 1, and the relationship between the remaining life of the circuit breaker and the cumulative arc energy at the kth breaking time can be described as the preset standard predicted life function as follows:

[0160] The preset standard predicted life function is specifically:

[0161] In the formula, r k represents the standard predicted life of the circuit breaker after the kth action.

[0162] In the embodiment of the application, the preset standard predicted life function is input by using the cumulative arc energy set and the total arc energy of the circuit breaker to perform calculation, and then the standard predicted life is output.

[0163] S15, determine the average prediction accuracy by using the training predicted life and the standard predicted life.

[0164] Further, S15 can include the following sub-steps:

[0165] S151, input the preset life prediction accuracy function by using the training predicted life and the standard predicted life to generate a life prediction accuracy set;

[0166] The preset life prediction accuracy rate function is specifically:

[0167] In the formula, α k represents the life prediction accuracy rate of the circuit breaker after the kth action, and the life prediction accuracy rate set is composed of k life prediction accuracy rates.

[0168] In the embodiment of the present application, the accuracy rate of the training prediction life obtained by the initial circuit breaker electrical life prediction model is calculated, the training prediction life and the standard prediction life are input into the preset life prediction accuracy rate function for operation, and the life prediction accuracy rate set is generated.

[0169] S152, inputting the life prediction accuracy rate set into the preset average prediction accuracy rate function to determine the average prediction accuracy rate;

[0170] The preset average prediction accuracy rate function is specifically:

[0171] In the formula, α represents the average prediction accuracy rate, and α i represents the life prediction accuracy rate of the circuit breaker after the ith action.

[0172] In the embodiment of the present application, the life prediction accuracy rate set is input into the preset average prediction accuracy rate function for operation to determine the average prediction accuracy rate.

[0173] S16, when the average prediction accuracy rate is greater than the preset standard prediction accuracy rate, a target circuit breaker electrical life prediction model is generated.

[0174] In the embodiment of the present application, the preset standard prediction accuracy rate is preferably 95%, if the average prediction accuracy rate is greater than 95%, the fitting function relationship between the single arc time and the arc energy and the key parameters thereof fitted at this time are stored, and the target circuit breaker electrical life prediction model is obtained accordingly.

[0175] Further, S16 further includes the following steps:

[0176] S17, when the average prediction accuracy rate is less than or equal to the preset standard prediction accuracy rate, then jump to S12.

[0177] Step 206, predicting the life of the circuit breaker to be predicted by the target circuit breaker electrical life prediction model to generate a life prediction result.

[0178] In the embodiment of the present application, the residual electrical life of the monitoring object (the circuit breaker to be predicted) is predicted and output according to the obtained target circuit breaker electrical life prediction model. The storage and calculation of the model can be realized by using a single-chip microcomputer, an upper computer or a digital signal processor as an execution unit, and only a simple sensor needs to be installed to measure the arc time and transmit it to the execution unit to predict the residual life of the circuit breaker and provide real-time operation state information of the circuit breaker for the staff.

[0179] It is worth mentioning that the present application is suitable for various applications of circuit breakers, and the model parameters need to be adjusted in time when the application scenarios or monitoring objects are different. In the case of high safety requirements or harsh environments (such as high-temperature environment, humid environment, etc.), the model parameters need to be corrected.

[0180] It should be noted that the model parameters refer to the parameters of the objective function of the target circuit breaker electrical life prediction model, and specifically refer to the constant coefficients in the function relationship formula (i.e. f(t arci )) obtained by fitting.

[0181] Further, based on the function fitting relationship obtained by S12, a circuit breaker electrical life prediction model of cumulative arc energy is established. Specifically, the function relationship obtained by S12 is used to replace the arc energy calculation method (preset single-arc energy function) in step 203, that is, only the single-arc time is used to calculate the single-arc energy, the cumulative arc energy is obtained, and the residual life is predicted. Until the kth action, the predicted residual electrical life of the circuit breaker is represented as follows.

[0182] The objective function of the target circuit breaker electrical life prediction model is specifically as follows.

[0183] In the formula, r predk represents the predicted residual life at the kth action, represents the target cumulative arc energy obtained by fitting until the ith action, and k represents the current breaking action number.

[0184] In the embodiment of the application, in response to a life test request of a test circuit breaker, a test running data set associated with the test circuit breaker is acquired in real time, the test running data set is input into a preset single arc function to generate a single arc time data set and a single arc energy data set, a function fitting method is used to perform function fitting on the single arc time data set and the single arc energy data set to generate a target circuit breaker electric life prediction model, and the target circuit breaker electric life prediction model is used to perform life prediction on a circuit breaker to be predicted to generate a life prediction result. The technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker and brings a safety hazard to the power system is solved. First, the relationship between the arc time and the arc energy in the breaking process of the circuit breaker is established, and the target circuit breaker electric life prediction model is constructed, so that the prediction result has high reliability and high accuracy. Second, the application avoids massive data storage and calculation, can realize fast prediction, and has simple requirements for data processors. Finally, the application can be integrated into a power transmission and transformation network operation platform or a digital signal processor, and real-time running data is input into the target circuit breaker electric life prediction model for real-time monitoring of the running state of the circuit breaker.

[0185] For ease of understanding, a specific application example is provided below:

[0186] The remaining effective electric life prediction object selected in this application example is a certain high-voltage circuit breaker, which can complete the switching on and off of a three-phase alternating current power transmission and transformation system.

[0187] It should be noted that the object of the application is applied to 500kV circuit breaker equipment in an alternating current main power grid. The high-voltage circuit breaker is only a specific object that can be selected.

[0188] Please refer to FIG. 5, which is a flow chart of the effective remaining electric life prediction method of the high-voltage circuit breaker in the application example of the application;

[0189] Step 1, input the device parameters and electric parameters (basic parameters) of the high-voltage equipment in the specific embodiment, and the specific parameters include: rated working voltage 550kV, rated working current 8kA, rated short-circuit breaking current 80kA, and rated peak withstand current 216kA.

[0190] An electric life experiment platform is built, and one voltage differential probe and one current probe are used to collect the arc voltage signal and the arc current signal between the contacts during the breaking of the high-voltage circuit breaker.

[0191] Combining Fig. 5, the relationship between single arc energy and single arc time is constructed. The calculation process of single arc energy is described. A period of time before the arc starting point is selected as t = 0. It can be seen from the figure that the arc starting time point t1 = 2.92 ms, the arc ending time point t2 = 10.07 ms, and the single arc time in this example is:

[0192] t arc = t2-t1 = 7.15 ms

[0193] The sampling rate of the differential probe used in the embodiment is fs = 180k, and the sampling interval is The single arc energy is:

[0194] In this embodiment, the allowable wear thickness of the high-voltage contact is defined as a = 3 mm. When the thickness reduction of the contact is detected to reach 3 mm, it is considered that the circuit breaker has failed, and the number of opening and closing times at this time is 8230. The relationship between the actual single arc time and the single arc energy obtained by statistics is shown in the scatter plot in Fig. 3. It can be seen that there is a clear correlation between them. The longer the single arc time, the greater the arc energy, and there is a nonlinear relationship between them. When the arc time is longer, the randomness and dispersion of the single arc energy are also greater.

[0195] Combining Fig. 4 and Fig. 5, the construction of the correlation data set of the cumulative arc energy of the circuit breaker and the remaining effective electrical life is described. The total electrical life of the high-voltage in the embodiment is 1, and the standard predicted life r k can be calculated by the following formula:

[0196] wherein n = 8230, represents the cumulative arc energy of the sample until the kth action, represents the cumulative arc energy at the failure time of the sample, which is also the total arc energy threshold of the reliable operation of the sample, E arci The calculation method of E is referred to the preset single arc energy function. The relationship between the cumulative arc energy and the remaining electrical life is shown in the solid line in Fig. 4.

[0197] Based on the actual single arc time and single arc energy data set shown in Fig. 3, a function relationship between the arc time and the arc energy is established. The single predicted arc energy E pred is calculated by using the obtained function relationship, and E arci in the above formula is replaced to calculate the predicted remaining electrical life. The function parameters are updated iteratively until the prediction average accuracy reaches 95%.

[0198] In this application example, the relationship between the single arc energy and the single arc time is fitted by using a quadratic polynomial, an exponential function and a Weibull distribution function as an example:

[0199] The relationship obtained by quadratic polynomial fitting is:

[0200] ΔE predd = p1t arc 2 + p2t arc + p3

[0201] wherein ΔE predd is the single-arc energy predicted by using quadratic polynomial, t arc is the actually measured single-arc time, p1, p2, p3 are function coefficients, and the optimal coefficient solution is p1=8.19x10 5 , p2=199.9, and p3=1.93, and the prediction average accuracy is 96%.

[0202] The relationship obtained by exponential function fitting is:

[0203] wherein ΔE prede is the single-arc energy predicted by using exponential function, t arc is the actually measured single-arc time, p, q, w, d are function coefficients, and the optimal coefficient solution is p=2.03x10 4 , q=754.6, w=2.03x10 4 , and d=754.6, and the prediction average accuracy is 93.5%.

[0204] The relationship obtained by Weibull function fitting is:

[0205] wherein ΔE predw is the single-arc energy predicted by using Weibull function, t arc is the actually measured single-arc time, a, b are function coefficients, and the optimal coefficient solution is a=2.68x10 6 and b=3.48, and the prediction average accuracy is 97.9%.

[0206] In the application example, the model predicted by Weibull function fitting has the highest average prediction accuracy, the fitting curve obtained is shown as a solid line in FIG. 3, and the relationship between the predicted electric life and the cumulative arc energy can be expressed by the following formula, and the prediction result is shown as a dashed line in FIG. 4.

[0207] It should be noted that the function relationship and function coefficients selected in the example are not the only method, and in the actual application process, the function type and function coefficients need to be adjusted according to the actual measurement results, and the function relationship with the smallest calculation amount is selected as the basis of the final prediction model under the condition of ensuring the prediction accuracy.

[0208] The application of the obtained prediction model in actual situations is explained below. The objective function of the obtained target circuit breaker electrical life prediction model, using a digital signal processor as the storage and calculation unit, inputs the model calculation code (which can calculate the objective function), the total arcing energy E pe = 1.38 x 105, the safety allowable range δ = 85%, selects the same type of high voltage as the test sample, installs an acceleration sensor at the moving contact part of the test sample, detects and records the start time and end time of each action of the test sample based on the change of acceleration, the difference between the two is the single arcing time, which is transmitted to the digital signal processor, the digital signal processor calculates the single arcing energy from this, and performs accumulation and storage, and calculates the predicted remaining life r predk at the same time, the prediction result is output to the outside world through a display screen. When the cumulative arcing energy value exceeds the safety threshold δE pe , the digital signal processor sends an alarm signal, which is displayed on the display screen, reminding the staff to overhaul and maintain. In order to verify the accuracy of the model, the test sample continues to run, and the predicted life ends at action 8036 times, and the actual contact wear reaches the safety allowable value of 3mm at action 8515 times. The prediction accuracy is 94%.

[0209] The prediction model used in the test sample in this embodiment is not unique. In the test sample in the embodiment, the arcing time is obtained by detecting the acceleration change of the moving contact using a sensor, and in actual application, other methods can be used to obtain the arcing time, such as the transient current method, intelligent detector detection, etc. In the test sample in the embodiment, a digital signal processor is selected as the storage and calculation unit, and in actual application, any tool that can achieve the required function can be selected according to the needs, such as a single-chip microcomputer, an upper computer, etc. The safety threshold δ = 85% set in the test sample in the embodiment is adjusted according to the safety requirements of the application situation in actual application, and in situations with high requirements for circuit breaker reliability, the safety threshold should be set lower.

[0210] In the actual application process, the model parameter values and the allowable wear thickness of the contact need to be corrected according to the specific circuit breaker type, specific product model, and specific application scenario, in order to improve the adaptability of the effective remaining electrical life prediction method of the high-voltage circuit breaker of the present application. It can be understood that this method has certain portability and can also be effective in changing objects and use scenarios, therefore, it should be considered to belong to the protection scope of the present application.

[0211] It needs to be additionally explained that the application is easily integrated into the power system main network operation and maintenance platform. Moreover, the method can not only independently realize the effective residual life prediction function of a certain circuit breaker, but also can centrally monitor and predict the life of all circuit breakers in a certain area. If the disclosed method of the application patent application is successfully applied, it will be beneficial to reduce the electric appliance fault repair rate and improve the operation reliability of the power system.

[0212] Please refer to Fig. 6, which is a structural block diagram of an effective residual electrical life prediction system of a high-voltage circuit breaker provided by the third embodiment of the application.

[0213] The effective residual electrical life prediction system of a high-voltage circuit breaker provided by the application comprises:

[0214] The response module 301 is configured to, in response to a life test request for a test circuit breaker, acquire a test operation data set associated with the test circuit breaker in real time.

[0215] The single-arc operation module 302 is configured to input the test operation data set into a preset single-arc function to generate a single-arc time data set and a single-arc energy data set.

[0216] The circuit breaker total arc energy module 303 is configured to input the single-arc energy data set into a preset circuit breaker total arc energy function to generate circuit breaker total arc energy.

[0217] The function fitting module 304 is configured to perform function fitting on the single-arc time data set and the single-arc energy data set based on a function fitting method to generate a target circuit breaker electrical life prediction model.

[0218] The life prediction module 305 is configured to perform life prediction on a to-be-predicted circuit breaker through the target circuit breaker electrical life prediction model to generate a life prediction result.

[0219] Further, the test operation data set comprises contact two-end arc voltage data in a circuit breaker action process, inter-contact arc current data, arc starting time data and arc extinguishing time data.

[0220] The arc starting time data and the arc extinguishing time data are determined by a mechanical factor determination method or a transient current method.

[0221] Further, the preset single-arc function comprises a single-arc time function and a single-arc energy function, and the single-arc operation module 302 comprises:

[0222] The single-arc time data set submodule is configured to input the arc starting time data and the arc extinguishing time data into the single-arc time function to generate a single-arc time data set.

[0223] The single-arc time function is specifically:

[0224] t arci = t 2i - t 1i

[0225] wherein, t arci represents the i-th single arc time data, wherein i = 1, 2, …, n, n represents the number of completed breaking actions, the single arc time data set is composed of n single arc time data, t 1i represents the i-th action arc ignition time data, t 2i represents the i-th action arc extinguishing time data.

[0226] The single arc energy data set sub-module is configured to input the single arc energy function with the arc ignition time data, the arc extinguishing time data, the two-end arc voltage data and the arc current data between contacts, and generate the single arc energy data set.

[0227] The single arc energy function is specifically:

[0228] wherein, ΔE arci represents the i-th single arc energy data, the single arc energy data set is composed of n single arc energy data, U i (t) represents the two-end arc voltage data at the i-th action t moment, I i (t) represents the arc current data between contacts at the i-th action t moment, and t represents the sampling interval.

[0229] Further, the preset circuit breaker total arc energy function is specifically:

[0230] wherein, E pe represents the circuit breaker total arc energy, and n represents the number of completed breaking actions.

[0231] Further, the function fitting module 304 comprises:

[0232] The reference prediction model sub-module is configured to obtain the basic parameters associated with the test circuit breaker, and input the basic parameters into the preset circuit breaker reference prediction model platform for matching to obtain the reference prediction model.

[0233] The initial circuit breaker electrical life prediction model sub-module is configured to perform function fitting on the reference prediction model based on the function fitting method, the single arc time data set and the single arc energy data set, and combine the circuit breaker total arc energy to construct the initial circuit breaker electrical life prediction model.

[0234] The function fitting relationship is specifically:

[0235] ΔEpredi = f(t arci )

[0236] In the formula, ΔE predi represents the single-arc energy obtained by function fitting through a function fitting method, f(t arci ) represents a function relationship with the optimal fitting effect;

[0237] The training prediction life submodule is configured to input an initial circuit breaker electrical life prediction model with a preset training operation data set to perform training, and generate a training prediction life.

[0238] The standard prediction life submodule is configured to determine a standard prediction life by using the single-arc energy data set and the total arc energy of the circuit breaker.

[0239] The average prediction accuracy submodule is configured to determine an average prediction accuracy by using the training prediction life and the standard prediction life.

[0240] The target circuit breaker electrical life prediction model submodule is configured to generate a target circuit breaker electrical life prediction model when the average prediction accuracy is greater than a preset standard prediction accuracy.

[0241] Further, the objective function of the target circuit breaker electrical life prediction model is specifically:

[0242] In the formula, r predk represents the predicted remaining life at the kth action, represents the target cumulative arc energy obtained by fitting up to the ith action, and k represents the current number of breaking actions.

[0243] Further, the standard prediction life submodule includes:

[0244] The cumulative arc energy set unit is configured to input a preset cumulative arc energy function with the single-arc energy data set to generate a cumulative arc energy set.

[0245] The preset cumulative arc energy function is specifically:

[0246] In the formula, E k represents the cumulative arc energy of the circuit breaker after the kth action, the cumulative arc energy set has k cumulative arc energies, and k represents the kth number of breaking actions.

[0247] The standard prediction life operation unit is configured to input a preset standard prediction life function with the cumulative arc energy set and the total arc energy of the circuit breaker to determine the standard prediction life.

[0248] The preset standard prediction life function is specifically:

[0249] In the formula, r k represents the standard predicted life of the circuit breaker after the kth action.

[0250] Further, the average prediction accuracy submodule comprises:

[0251] The life prediction accuracy set unit is configured to input the training prediction life and the standard prediction life into a preset life prediction accuracy function to generate a life prediction accuracy set.

[0252] The preset life prediction accuracy function is specifically:

[0253] In the formula, α k represents the life prediction accuracy of the circuit breaker after the ith action.

[0254] The average prediction accuracy operation unit is configured to input the life prediction accuracy set into a preset average prediction accuracy function to determine the average prediction accuracy.

[0255] The preset average prediction accuracy function is specifically:

[0256] In the formula, α represents the average prediction accuracy, and α i represents the life prediction accuracy of the circuit breaker after the ith action.

[0257] In the embodiment of the present application, in response to a life test request for a test circuit breaker, a test running data set associated with the test circuit breaker is acquired in real time, the test running data set is input into a preset single-arc function to generate a single-arc time data set and a single-arc energy data set, a function fitting method is used to perform function fitting on the single-arc time data set and the single-arc energy data set to generate a target circuit breaker electrical life prediction model, the target circuit breaker electrical life prediction model is used to predict the life of a circuit breaker to be predicted to generate a life prediction result; the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker and brings a safety hazard to the power system is solved; first, the relationship between the arc time and the arc energy in the breaking process of the circuit breaker is established, the target circuit breaker electrical life prediction model is constructed, the prediction result has high reliability and high accuracy, second, the present application avoids massive data storage and calculation, can realize fast prediction effect, and has simple requirements for data processors, and finally, can be integrated into a power transmission and transformation network operation and maintenance platform or a digital signal processor, real-time running data is input into the target circuit breaker electrical life prediction model for real-time monitoring of the running state of the circuit breaker.

[0258] Please refer to FIG. 7, which shows a structural block diagram of a computer device according to an embodiment of the present application.

[0259] An electronic device according to an embodiment of the present application comprises a memory 401 and a processor 402, the memory 401 storing a computer program, the computer program being executed by the processor 402 to cause the processor 402 to perform the method for predicting the effective residual electrical life of a high voltage circuit breaker according to any of the above described embodiments.

[0260] The memory 401 can be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk or a ROM. The memory 401 has a storage space 403 for program codes 413 for performing any of the method steps described above. For example, the storage space 403 for program codes can comprise individual program codes 413 for implementing the various steps in the above described methods, respectively. These program codes can be read from or written to one or more computer program products. These computer program products comprise program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. The program codes can be compressed, for example, in a suitable form. These codes, when run by a computing processing device, cause the computing processing device to perform the individual steps in the above described methods. These program codes can be read from or written to one or more computer program products. These computer program products comprise program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. The program codes can be compressed, for example, in a suitable form. These codes, when run by a computing processing device, cause the computing processing device to perform the individual steps in the above described direct current charging pile control method.

[0261] The embodiment of the present application further provides a computer readable storage medium, having stored thereon a computer program, the computer program being executed by a processor to implement the method for predicting the effective residual electrical life of a high voltage circuit breaker according to any of the above described embodiments.

[0262] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above described system, device and unit can refer to the corresponding processes in the above described method embodiments, which will not be described here.

[0263] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the division of the units is only a logical function division, and there can be another division manner for the actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be electric, mechanical or in other forms.

[0264] The units described as separated components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0265] In addition, each functional unit in the various embodiments of the present application can be integrated in a processing unit, or each unit can exist physically as a separate unit, or two or more units can be integrated in one unit. The integrated unit can be implemented in the form of hardware, or in the form of a software functional unit.

[0266] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solutions of the present application essentially, or the part that contributes to the prior art, or all or a part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in the various embodiments of the present application. The foregoing storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, and various media that can store program codes.

[0267] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of predicting an effective residual electrical life of a high voltage circuit breaker, characterized by, The method comprises the following steps: in response to a life test request for a test circuit breaker, real-time acquisition of a test running data set associated with the test circuit breaker; inputting the test running data set into a preset single-arc function to generate a single-arc time data set and a single-arc energy data set; inputting the single-arc energy data set into a preset total arc energy function of the circuit breaker to generate a total arc energy of the circuit breaker; function fitting of the single-arc time data set and the single-arc energy data set, and construction of a target circuit breaker electric life prediction model in combination with the total arc energy of the circuit breaker; life prediction of a to-be-predicted circuit breaker through the target circuit breaker electric life prediction model to generate a life prediction result.

2. The method of claim 1, wherein the method further comprises: The test running data set comprises arc voltage data between contacts during a circuit breaker action process, arc current data between contacts, arc starting time data and arc extinguishing time data; wherein the arc starting time data and the arc extinguishing time data are determined by a mechanical factor determination method or a transient current method.

3. The method for predicting the effective remaining electrical life of a high-voltage circuit breaker according to claim 2, characterized in that, The preset single-arc function comprises a single-arc time function and a single-arc energy function, and the step of inputting the test running data set into the preset single-arc function to generate a single-arc time data set and a single-arc energy data set comprises: inputting the arc starting time data and the arc extinguishing time data into the single-arc time function to generate a single-arc time data set; The single-arc time function is specifically: t arci = t 2i -t 1i wherein t arci represents the i-th single arc time data, wherein i = 1, 2,..., n, n represents the number of times of completing the breaking action, the single arc time data set is composed of n single arc time data, t 1i represents the i-th action time data of the arc starting time, t 2i represents the i-th action time data of the arc extinguishing time; inputting the arc starting time data, the arc extinguishing time data, the arc voltage data between contacts and the arc current data between contacts into a single-arc energy function to generate a single-arc energy data set; The single-arc energy function is specifically: wherein ΔE arci represents the i-th single arc energy data, the single arc energy data set consisting of n single arc energy data, U i (t) represents the i-th two-terminal arc voltage data at time t, I i (t) represents the i-th inter-contact arc current data at time t, t represents the sampling interval.

4. The method of claim 1, wherein the method further comprises: The preset total arc energy function of the circuit breaker is specifically: In the formula, E pe represents the total arc energy of the circuit breaker, and n represents the number of times of completing the breaking operation.

5. The method of claim 1, wherein the method further comprises: The step of function fitting of the single-arc time data set and the single-arc energy data set, and construction of a target circuit breaker electric life prediction model in combination with the total arc energy of the circuit breaker comprises: acquisition of basic parameters associated with the test circuit breaker, and inputting the basic parameters into a preset circuit breaker reference prediction model platform for matching to obtain a reference prediction model; function fitting of the single-arc time data set and the single-arc energy data set to the reference prediction model based on a function fitting method, and construction of an initial circuit breaker electric life prediction model in combination with the total arc energy of the circuit breaker; The function fitting relationship is specifically: ΔE predi = f(t arci ) In the formula, ΔE predi single-arc energy obtained by function fitting by a function fitting method amount, f(t arci ) represents the function relationship with the best fitting effect; inputting a preset training running data set into the initial circuit breaker electric life prediction model for training to generate a training prediction life; determination of a standard prediction life by using the single-arc energy data set and the total arc energy of the circuit breaker; determination of an average prediction accuracy by using the training prediction life and the standard prediction life; when the average prediction accuracy is greater than a preset standard prediction accuracy, a target circuit breaker electric life prediction model is generated.

6. The method of claim 5, wherein the effective residual electrical life of the high voltage circuit breaker is predicted based on the estimated electrical life of the high voltage circuit breaker and the estimated mechanical life of the high voltage circuit breaker. The objective function of the target circuit breaker electrical life prediction model is specifically: In the formula, r predk represents the predicted remaining life at the kth action, The target cumulative arc energy obtained by fitting is represented by i, and k represents the current number of breaking actions.

7. The method for predicting the effective remaining electrical life of a high-voltage circuit breaker according to claim 5, characterized in that, The step of determining the standard prediction life by using the single-arc energy data set and the total arc energy of the circuit breaker comprises: inputting the single-arc energy data set into a preset cumulative arc energy function to generate a cumulative arc energy set; The preset accumulated arcing energy function is specifically: In the formula, E k represents the cumulative arc energy of the circuit breaker after the kth operation, the cumulative arc energy is composed of k cumulative arc energies, and k represents the number of kth breaking operations. The cumulative arc energy set and the circuit breaker total arc energy input preset standard prediction life function are used to determine the standard prediction life; The preset standard life prediction function is specifically: In the formula, r k represents the standard predicted life of the circuit breaker after the kth operation.

8. The method of claim 5, wherein the effective residual life of the high-voltage circuit breaker is predicted based on the number of times the high-voltage circuit breaker is operated, the number of times the high-voltage circuit breaker is operated, and the number of times the high-voltage circuit breaker is operated. The step of determining the average prediction accuracy using the training prediction life and the standard prediction life comprises: The training prediction life and the standard prediction life are input into a preset life prediction accuracy function to generate a life prediction accuracy set; The preset service life prediction accuracy function is specifically: In the formula, α k indicates the life prediction accuracy of the circuit breaker after the kth action, and the life prediction accuracy set is composed of k life prediction accuracies. The life prediction accuracy set is input into a preset average prediction accuracy function to determine the average prediction accuracy; The preset average prediction accuracy function is specifically: In the formula, a represents the average prediction accuracy, a i represents the life prediction accuracy of the circuit breaker after the i th action.

9. A system for predicting the effective residual electrical life of a high voltage circuit breaker, characterized by, Comprise: In response to a life test request for a test circuit breaker, a response module is configured to acquire a test running data set associated with the test circuit breaker in real time; A single arc operation module is configured to input the test running data set into a preset single arc function to generate a single arc time data set and a single arc energy data set; A circuit breaker total arc energy module is configured to input the single arc energy data set into a preset circuit breaker total arc energy function to generate circuit breaker total arc energy; A function fitting module is configured to perform function fitting on the single arc time data set and the single arc energy data set based on a function fitting method to generate a target circuit breaker electrical life prediction model; A life prediction module is configured to perform life prediction on a to-be-predicted circuit breaker through the target circuit breaker electrical life prediction model to generate a life prediction result.

10. An electronic device, comprising: The computer program is executed to implement the high-voltage circuit breaker effective residual electrical life prediction method according to any one of claims 1-8.

11. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed to implement the high-voltage circuit breaker effective residual electrical life prediction method according to any one of claims 1-8.

Images