An effective remaining electrical life prediction method and system for a high-voltage circuit breaker

Abstract

The present invention relates to the technical field of high-voltage power transmission and transformation protection equipment, and discloses an effective remaining electrical life prediction method and system for a high-voltage circuit breaker. The electrical life test of the circuit breaker is carried out, and a correlation data set between the single arcing time and the single arcing energy is constructed. The cumulative arcing energy is used to replace the contact wear degree to characterize whether the circuit breaker fails. The function fitting is used to construct the relationship between the single arcing energy and the single arcing time. Based on this, an effective remaining electrical life prediction method for the high-voltage circuit breaker is formed. Only simple data needs to be detected to realize the rapid and accurate prediction of the remaining life of the circuit breaker, which can provide guarantee for the reliable operation of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of high-voltage power transmission and transformation protection equipment, and particularly relates to an effective remaining electrical life prediction method and system for a high-voltage circuit breaker. Background Art

[0002] A circuit breaker is a common switching device in the power system, which can connect or disconnect normal load current and overload current. With the large-scale access of loads and the increasing complexity of the power grid network structure, higher requirements are put forward for the operation reliability and service life of the circuit breaker. With the increase in the number of operations, the accumulation of wear and aging of the circuit breaker will lead to a decline in its life and reliability. The main indicators reflecting its reliability are mechanical life and electrical life. The mechanical life of the circuit breaker is always designed to be much higher than the electrical life. Therefore, most of the discussions on its life prediction refer to the electrical life. When the circuit breaker switches the current, material sputtering and transfer will occur between the contacts along with the arc, resulting in wear and loss of the contact material, which is the main reason for the reduction of the electrical life. The decline in the reliability of the circuit breaker will pose a great threat and risk to the safe operation of the power grid. The failure to cut off the fault is very likely to cause damage to important equipment and even trigger a fire. Conducting condition monitoring on the circuit breaker in real-time operation and accurately predicting its remaining effective life can guide the staff to perform timely maintenance and replacement of the circuit breaker, ensuring the reliable operation of the power system.

[0003] In practical applications, the method of regular replacement is often used to ensure the reliability of the circuit breaker. This method uses the service time as a measurement standard and replaces the circuit breaker that exceeds the safe service period. However, due to the different operating frequencies and breaking current magnitudes of the circuit breaker in different scenarios, some circuit breakers with fewer breaking times and smaller connected loads still have a relatively long remaining life within the safe period. Replacing them at this time will cause waste of resources. Relying on the cumulative number of times to judge the remaining life of the circuit breaker is also a common life prediction method. However, the loss of the contact during a single operation is closely related to the arcing time and current magnitude, with great uncertainty. Relying on the cumulative number of times to judge the remaining life has low reliability, which may cause waste of resources by prematurely replacing equipment with good operating conditions, or may not be able to detect equipment with serious deterioration in time, posing a safety hazard to the power system. At present, there are also studies on predicting the circuit breaker by relying on vibration signals combined with artificial intelligence algorithms, but it is necessary to install a complex sensor system, which increases the cost and is easily interfered by the environment. Therefore, a technology is needed to realize the real-time life prediction of the circuit breaker. Summary of the Invention

[0004] The present invention provides an effective remaining electrical life prediction method and system for a high-voltage circuit breaker, which solves the technical problem that the existing circuit breaker life prediction methods cannot accurately and quickly detect the life of the circuit breaker, posing a safety hazard to the power system.

[0005] A method for predicting the effective remaining electrical life of a high-voltage circuit breaker provided by the first aspect of the present invention includes:

[0006] In response to a life test request for a test circuit breaker, the test operation data set associated with the test circuit breaker is obtained in real time;

[0007] Using the test operation data set to input a preset single arcing function to generate a single arcing time data set and a single arcing energy data set;

[0008] Using the single arcing energy data set to input a preset total arc energy function of the circuit breaker to generate the total arc energy of the circuit breaker;

[0009] Performing function fitting on the single arcing time data set and the single arcing energy data set, and combining the total arc energy of the circuit breaker to construct a target circuit breaker electrical life prediction model;

[0010] Performing life prediction on the circuit breaker to be predicted through the target circuit breaker electrical life prediction model to generate a life prediction result.

[0011] Optionally, the test operation data set includes arc voltage data at both ends of the contacts during the operation of the circuit breaker, arc current data between the contacts, arcing start time data, and arc extinction time data;

[0012] Among them, the arcing start time data and the arc extinction time data are determined by a mechanical factor measurement method or a transient current method.

[0013] Optionally, the preset single arcing function includes a single arcing time function and a single arcing energy function. The step of using the test operation data set to input the preset single arcing function to generate a single arcing time data set and a single arcing energy data set includes:

[0014] Using the arcing start time data and the arc extinction time data to input the single arcing time function to generate a single arcing time data set;

[0015] The single arcing time function is specifically:

[0016]

[0017] In the formula, represents the th single arcing time data, where , represents the number of opening operations completed, and the single arcing time data set is composed of pieces of the single arcing time data, represents the arcing start time data at the th operation, representing the arc extinction moment data at the th operation;

[0018] Inputting the arc ignition start moment data, the arc extinction moment data, the arc voltage data at both ends, and the arc current data between the contacts into a single - arc energy function to generate a single - arc energy data set;

[0019] The specific form of the single - arc energy function is:

[0020]

[0021] In the formula, represents the th single - arc energy data, and the single - arc energy data set is composed of such single - arc energy data, represents the arc voltage data at both ends at the th operation moment, represents the arc current data between the contacts at the th operation moment, represents the sampling interval.

[0022] Optionally, the specific form of the preset total arc energy function of the circuit breaker is:

[0023]

[0024] In the formula, represents the total arc energy of the circuit breaker, represents the number of opening operations 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 arc energy of the circuit breaker includes:

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

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

[0028] The specific function fitting relationship is:

[0029]

[0030] In the formula, represents the single arcing energy obtained by function fitting through the function fitting method, represents the function relationship with the optimal fitting effect;

[0031] Use the preset training operation data set to input the initial breaker electrical life prediction model for training to generate a training predicted life;

[0032] Use the single arcing energy data set and the total arcing energy of the breaker to determine the standard predicted life;

[0033] Use the training predicted life and the standard predicted life to determine the average prediction accuracy;

[0034] When the average prediction accuracy is greater than the preset standard prediction accuracy, generate a target breaker electrical life prediction model.

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

[0036]

[0037] In the formula, represents the predicted remaining life at the th action, represents the target cumulative arcing energy obtained by fitting up to the th action, represents the current number of opening operations.

[0038] Optionally, the step of using the single arcing energy data set and the total arcing energy of the breaker to determine the standard predicted life includes:

[0039] Use the single arcing energy data set to input a preset cumulative arcing energy function to generate a cumulative arcing energy set;

[0040] The preset cumulative arcing energy function is specifically:

[0041]

[0042] In the formula, represents the cumulative arcing energy of the breaker after the th action, and the cumulative arcing energy set is composed of such cumulative arcing energies, represents the th opening operation number;

[0043] Use the cumulative arcing energy set and the total arcing energy of the breaker to input a preset standard predicted life function to determine the standard predicted life;

[0044] The specific preset standard predicted life function is as follows:

[0045]

[0046] In the formula, represents the standard predicted life of the circuit breaker after the -th operation.

[0047] Optionally, the step of determining the average prediction accuracy rate by using the trained predicted life and the standard predicted life includes:

[0048] Inputting the trained predicted life and the standard predicted life into a preset life prediction accuracy rate function to generate a set of life prediction accuracy rates;

[0049] The specific preset life prediction accuracy rate function is as follows:

[0050]

[0051] In the formula, represents the life prediction accuracy rate of the circuit breaker after the -th operation, and the set of life prediction accuracy rates is composed of such life prediction accuracy rates;

[0052] Inputting the set of life prediction accuracy rates into a preset average prediction accuracy rate function to determine the average prediction accuracy rate;

[0053] The specific preset average prediction accuracy rate function is as follows:

[0054]

[0055] In the formula, represents the average prediction accuracy rate, represents the life prediction accuracy rate of the circuit breaker after the -th operation.

[0056] A high-voltage circuit breaker effective remaining electrical life prediction system provided in the second aspect of the present invention includes:

[0057] A response module, configured to, in response to a life test request for a test circuit breaker, obtain in real time a test operation data set associated with the test circuit breaker;

[0058] A single-arc operation module, 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;

[0059] The total arc energy module of the circuit breaker is used to input the single-arc ignition energy data set into a preset total arc energy function of the circuit breaker to generate the total arc energy of the circuit breaker;

[0060] The function fitting module is used to perform function fitting on the single-arc ignition time data set and the single-arc ignition energy data set based on the function fitting method to generate a target electrical life prediction model of the circuit breaker;

[0061] The life prediction module is used to perform life prediction on the circuit breaker to be predicted through the target electrical life prediction model of the circuit breaker to generate a life prediction result.

[0062] An electronic device provided in the third aspect of the present invention includes a memory and a processor. A computer program is stored in the memory. When the computer program is executed by the processor, the processor executes the steps of the effective remaining electrical life prediction method of the high-voltage circuit breaker as described in any one of the above.

[0063] A computer-readable storage medium provided in the fourth aspect of the present invention has a computer program stored thereon. When the computer program is executed, it implements the effective remaining electrical life prediction method of the high-voltage circuit breaker as described in any one of the above.

[0064] It can be seen from the above technical solutions that the present invention has the following advantages:

[0065] In response to a life test request for a test circuit breaker, the present invention obtains in real time a test operation data set associated with the test circuit breaker, inputs the test operation data set into a preset single-arc ignition function to generate a single-arc ignition time data set and a single-arc ignition energy data set, performs function fitting on the single-arc ignition time data set and the single-arc ignition energy data set based on the function fitting method to generate a target electrical life prediction model of the circuit breaker, and performs life prediction on the circuit breaker to be predicted through the target electrical life prediction model of the circuit breaker to generate a life prediction result; solving the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker, bringing potential safety hazards to the power system.

[0066] 1) The present invention comprehensively considers the relationship between the cumulative arc energy and the contact wear mass, and uses electrical signal parameters to characterize the contact mechanical parameters, which is simple and easy to implement.

[0067] 2) The present invention establishes the relationship between the arc ignition time and the arc ignition energy during the opening process of the circuit breaker, constructs a life prediction model, and the prediction result has high reliability and high accuracy.

[0068] 3) The feature extraction content involved in the present invention is simple, the process is easy, the required sensors are small in size and easy to install, and the impact on the normal operation of the circuit breaker is small.

[0069] 4) The present invention avoids massive data storage and calculation, can achieve the effect of rapid prediction, and has simple requirements for the data processor.

[0070] 5) The present invention can be integrated into the operation and maintenance platform of the power transmission and transformation network or the digital signal processor for real-time monitoring of the operating state of the circuit breaker.

[0071] 6) The present invention has a certain portability and can be applied to different objects or scenarios for predicting the remaining service life of the circuit breaker. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0073] Figure 1 It is a flowchart of the steps of a method for predicting the effective remaining service life of a high-voltage circuit breaker provided in Embodiment 1 of the present invention;

[0074] Figure 2 It is a flowchart of the steps of a method for predicting the effective remaining service life of a high-voltage circuit breaker provided in Embodiment 2 of the present invention;

[0075] Figure 3 It is a schematic diagram of the fitting function of the relationship between the single-arc energy and the arcing time provided in the embodiment of the present invention;

[0076] Figure 4 It is a schematic diagram of the comparison between the actual service life and the predicted service life provided in the embodiment of the present invention;

[0077] Figure 5 It is a flowchart of the method for predicting the effective remaining service life of the high-voltage circuit breaker in the application example of the present invention.

[0078] Figure 6 It is a structural block diagram of a system for predicting the effective remaining service life of a high-voltage circuit breaker provided in Embodiment 3 of the present invention.

[0079] Figure 7 It is a schematic diagram of the framework of an electronic device provided in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0080] The embodiments of the present invention provide a method and a system for predicting the effective remaining service life of a high-voltage circuit breaker, which are used to solve the technical problem that the existing methods for predicting the service life of a circuit breaker cannot accurately and quickly detect the service life of the circuit breaker, bringing potential safety hazards to the power system.

[0081] In order to make the object, features, and advantages of the present invention more obvious and understandable, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the following described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0082] In view of the existing defects, the present invention provides an effective remaining electrical life prediction method and system for a high-voltage circuit breaker, and its main purpose is to be applied to the protection equipment in the high-voltage power distribution and utilization system.

[0083] Another purpose thereof is to propose an effective remaining electrical life prediction method for a high-voltage circuit breaker, realizing accurate, reliable, and rapid circuit breaker life prediction and deterioration degree evaluation, and providing guarantee for the safe operation of the high-voltage power distribution and utilization system.

[0084] Another purpose thereof is to propose an effective remaining electrical life prediction method for a high-voltage circuit breaker, guiding the maintenance and replacement of the circuit breaker in the system, making the circuit breaker be utilized to the maximum extent, and at the same time timely performing maintenance or replacement on the circuit breaker that exceeds the safe service life, providing a reliable reference for the maintenance work of the staff.

[0085] Another purpose thereof is to form a system for predicting the remaining effective life of the circuit breaker, performing centralized status monitoring and operation and maintenance management on the circuit breaker equipment in the area.

[0086] Please refer to Figure 1 , Figure 1 which is the step flow chart of an effective remaining electrical life prediction method for a high-voltage circuit breaker provided in Embodiment 1 of the present invention.

[0087] An effective remaining electrical life prediction method for a high-voltage circuit breaker provided by the present invention includes:

[0088] Step 101, in response to a life test request for a test circuit breaker, obtain the associated test operation data set of the test circuit breaker in real time.

[0089] The life test request refers to the request information for conducting the electrical life experiment test of the circuit breaker with the test circuit breaker as the prototype.

[0090] The test operation data set refers to the real-time acquisition data of the arc voltage at both ends of the contact, the arc current between the contacts, the starting moment of arcing, and the extinguishing moment of the arc during the operation of the test circuit breaker, and is classified and integrated according to the acquisition time and data type to form a data set.

[0091] In an embodiment of the present invention, in response to receiving a request message for conducting a circuit breaker electrical life experiment test with a test circuit breaker as a prototype, a real-time acquisition data set of the arc voltage at both ends of the contacts, the arc current between the contacts, the arc ignition start time, and the arc extinction time during the operation process of the circuit breaker associated with the test circuit breaker is obtained.

[0092] Step 102: 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.

[0093] The preset single-arc function refers to a single-arc time function and a single-arc energy function, which are used to calculate the single-arc time and single-arc energy of the circuit breaker.

[0094] The single-arc time data set refers to a data set composed of multiple single-arc times generated by inputting the test operation data set into the single-arc time function for calculation.

[0095] The single-arc energy data set refers to a data set composed of multiple single-arc energies generated by inputting the test operation data set into the single-arc energy function for calculation.

[0096] In an embodiment of the present invention, the test operation data set is input into a preset single-arc function 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 respectively.

[0097] Step 103: Input the single-arc energy data set into a preset total arc energy function of the circuit breaker to generate the total arc energy of the circuit breaker.

[0098] In an embodiment of the present invention, the single-arc energy data set is input into a preset total arc energy function of the circuit breaker for calculation to generate the total arc energy of the circuit breaker.

[0099] Step 104: Perform function fitting on the single-arc time data set and the single-arc energy data set, and construct a target circuit breaker electrical life prediction model in combination with the total arc energy of the circuit breaker.

[0100] Function fitting refers to performing function fitting based on the calculated single-arc time data set and single-arc energy data set to establish a functional relationship between the arc time and the arc energy.

[0101] The target circuit breaker electrical life prediction model refers to continuously training with the established functional relationship between the arc time and the arc energy as the objective function of the model, and constructing an electrical life prediction model in combination with the total arc energy of the circuit breaker.

[0102] In an embodiment of the present invention, a functional relationship between the arcing time and the arcing energy is established by using a function fitting method, and a target circuit breaker electrical life prediction model is constructed in combination with the total arc energy of the circuit breaker.

[0103] Step 105: Perform life prediction on the circuit breaker to be predicted through the target circuit breaker electrical life prediction model, and generate a life prediction result.

[0104] In an embodiment of the present invention, when receiving the operation data to be predicted of the circuit breaker to be predicted, the operation data to be predicted is input into the target circuit breaker electrical life prediction model for life prediction, and the life prediction result of the circuit breaker to be predicted is output.

[0105] In an embodiment of the present invention, in response to a life test request for a test circuit breaker, a test operation data set associated with the test circuit breaker is obtained in real time. The test operation data set is input into a preset single arcing function to generate a single arcing time data set and a single arcing energy data set. Based on the function fitting method, the single arcing time data set and the single arcing energy data set are subjected to function fitting to generate a target circuit breaker electrical life prediction model. The target circuit breaker electrical life prediction model is used to perform life prediction on the circuit breaker to be predicted, and a life prediction result is generated; the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker, bringing potential safety hazards to the power system is solved; first, by establishing the relationship between the arcing time and the arcing energy during the opening process of the circuit breaker, a target circuit breaker electrical life prediction model is constructed, making the prediction result have high reliability and high accuracy. Secondly, the present invention avoids massive data storage and calculation, can achieve the effect of rapid prediction, and has simple requirements for the data processor. Finally, it can be integrated into the operation and maintenance platform of the transmission and transformation power grid or the digital signal processor. By collecting operation data in real time and inputting it into the target circuit breaker electrical life prediction model, it is used for real-time monitoring of the operation state of the circuit breaker.

[0106] Please refer to Figure 2 , Figure 2 which is a step flowchart of an effective remaining electrical life prediction method for a high-voltage circuit breaker provided in the second embodiment of the present invention.

[0107] An effective remaining electrical life prediction method for a high-voltage circuit breaker provided by the present invention includes:

[0108] Step 201: In response to a life test request for a test circuit breaker, obtain the test operation data set associated with the test circuit breaker in real time.

[0109] In an embodiment of the present invention, the specific implementation process of step 201 is similar to that of step 101, and will not be elaborated here.

[0110] Furthermore, the test run data set includes the arc voltage data at both ends of the contacts during the breaker operation process, the arc current data between the contacts, the arcing start time data, and the arcing extinction time data;

[0111] Among them, the arcing start time data and the arcing extinction time data are determined by the mechanical factor measurement method or the transient current method.

[0112] It should be noted that for the electrical life test of the breaker, a test run data set of the single arcing time and the single arcing energy of the breaker needs to be obtained. The test run data set includes the arc voltage data at both ends of the contacts during the breaker operation process , the arc current data between the contacts , the arcing start time data and the arcing extinction time data ; it can be collected by measuring instruments such as voltage probes, current probes (Rogowski coils), oscilloscopes, etc., or the values of the intelligent monitoring instruments of the branch where the breaker is located can be read.

[0113] It should be noted that for the specific definition of the single arcing time, assume that in a certain opening operation of the breaker, the arcing start time is , and the arcing extinction time is , then the single arcing time t can be expressed by the following formula:

[0114]

[0115] During the breaker opening process, to achieve the tripping action, it is necessary to first overcome the pressure between the moving and static contacts, and there is a short pause time. However, since the time difference from when the breaker receives the tripping signal to when the arc starts to generate is very small and can be ignored compared to the entire arcing time, it can be considered that the moment when the breaker receives the opening command is , and the arcing extinction moment can be determined by monitoring the change of the moving contact acceleration through a sensor.

[0116] It is worth mentioning that the mechanical factor measurement method means that first, the moment when the breaker receives the opening command is used as the arcing start time, secondly, the change of the moving contact acceleration is monitored through an acceleration sensor to determine the arcing extinction time, and finally, the difference between the arcing start time and the arcing extinction time is calculated to determine the single arcing time.

[0117] Calculating the arcing time according to the mechanical factor is not the only method. The arcing start time data and the arcing extinction time data can also be determined by the transient current method.

[0118] The transient current method refers to that after monitoring the current signal during the opening of the circuit breaker, low-pass filtering is performed and then data fitting is carried out to predict the current change in a short time, and the actual current is compared to obtain the starting and ending points of the breaking, and the difference between the two is the arcing time.

[0119] It should be noted that the arcing start time data and arcing extinction time data in this embodiment can be determined by the mechanical factor measurement method or the transient current method. By obtaining data through two methods, the data source is wider. When performing data verification, the data obtained through the two methods can be mutually verified, making the prediction result more accurate.

[0120] Furthermore, the preset single arcing function includes a single arcing time function and a single arcing energy function.

[0121] Step 202: Input the arcing start time data and arcing extinction time data into the single arcing time function to generate a single arcing time data set;

[0122] The single arcing time function is specifically:

[0123]

[0124] In the formula, represents the th single arcing time data, where , represents the number of opening operations completed, and the single arcing time data set is composed of single arcing time data, represents the arcing start time data at the th operation, represents the arcing extinction time data at the th operation.

[0125] In the embodiment of the present invention, the arcing start time data and arcing extinction time data are input into the single arcing time function to generate a single arcing time data set.

[0126] Step 203: Input the arcing start time data, arcing extinction time data, arc voltage data at both ends, and arc current data between the contacts into the single arcing energy function to generate a single arcing energy data set;

[0127] It is worth mentioning that the single arcing energy is specifically defined, and the single arcing energy (assuming the i-th time) can be calculated by the following formula:

[0128]

[0129] In the formula, is the arcing energy of the th circuit breaker opening, is the starting moment of arcing for the th operation, is the ending moment of arcing, is the arc voltage, is the arc current.

[0130] Since signal acquisition is a discrete time-consuming process with a sampling interval, the single-arc energy during actual calculation is obtained from the following single-arc energy function.

[0131] The specific single-arc energy function is as follows:

[0132]

[0133] In the formula, represents the th single-arc energy data. The single-arc energy data set consists of pieces of single-arc energy data, represents the arc voltage data at both ends at the th operation moment, represents the arc current data between the contacts at the th operation moment, represents the sampling interval.

[0134] In the embodiment of the present invention, the starting moment data of arcing, the ending moment data of arcing, the arc voltage data at both ends, and the arc current data between the contacts are input into the single-arc energy function to generate a single-arc energy data set.

[0135] Step 204: Input the single-arc energy data set into a preset total arc energy function of the circuit breaker to generate the total arc energy of the circuit breaker.

[0136] The specific preset total arc energy function of the circuit breaker is as follows:

[0137]

[0138] In the formula, represents the total arc energy of the circuit breaker, represents the number of opening operations completed.

[0139] It should be noted that during the electrical life experiment, the wear condition of the circuit breaker contacts is used as the criterion for judging the end of the circuit breaker life. Specifically, if the allowable wear thickness of the circuit breaker contacts is , when the wear thickness of the sample contacts during the life experiment is greater than or equal to , the circuit breaker is considered to have failed. Assuming that n opening operations have been completed at this time, the total arc energy of the circuit breaker is:

[0140]

[0141] Obtained As a new safety threshold, it is used to judge the degradation situation of the circuit breaker and whether its life has ended.

[0142] It should be noted that the total arc energy of the circuit breaker is used to replace the allowable wear thickness as the criterion for judging the end of the circuit breaker's life for a principle explanation. When the circuit breaker makes a load-breaking operation, an arc is generated between the contacts, accompanied by a large amount of light and heat, which is a process of energy transfer. The generation of the arc is essentially a gas discharge phenomenon. When there is sufficient current and voltage between the contacts at the moment when the circuit breaker contacts are separated, the air between the contacts is broken down, resulting in a self-sustaining discharge phenomenon, and the current gas conducts electricity. During the process of arc generation, the contact material will be worn, and the magnitude of this wear is positively correlated with the energy generated by the arc, that is, the magnitude of the current and voltage. Therefore, the quality loss of the contacts can be quantified by the arc energy.

[0143] It is worth mentioning that the present invention comprehensively considers the relationship between the cumulative arc energy and the mass loss of the contacts, uses the cumulative arc energy to replace the degree of contact wear to characterize whether the circuit breaker fails, and uses electrical signal parameters to characterize the mechanical parameters of the contacts, which is simple and easy to implement.

[0144] In the embodiment of the present invention, a single-arc energy data set is input into a preset total arc energy function of the circuit breaker for operation to generate the total arc energy of the circuit breaker.

[0145] Step 205: Perform function fitting on the single-arc time data set and the single-arc energy data set, and construct a target circuit breaker electrical life prediction model in combination with the total arc energy of the circuit breaker.

[0146] Further, step 205 may include the following sub-steps:

[0147] S11: Obtain the basic parameters associated with the test circuit breaker, and input the basic parameters into a preset circuit breaker benchmark prediction model platform for matching to obtain a benchmark prediction model.

[0148] In the embodiment of the present invention, the basic parameters of the test circuit breaker are input, and the basic parameters include equipment parameters and electrical parameters. Specifically, the basic parameters include the rated operating voltage, rated operating current, rated short-circuit breaking current, and rated peak withstand current of the circuit breaker. According to the actual application scenario of the circuit breaker, other parameters are selectively input.

[0149] It is worth mentioning that the preset circuit breaker benchmark prediction model platform refers to a benchmark prediction model associated with multiple prediction functions with different specific fitting function types and function parameters pre-built. Each benchmark prediction model corresponds to a high-voltage circuit breaker with certain determined basic parameters. When the user inputs the basic parameters of the high-voltage circuit breaker to be detected, the system automatically matches the corresponding benchmark prediction model associated with the prediction function. The input of the basic parameters here is for the purpose of matching during subsequent function fitting. Circuit breakers with different parameters may have different applicable model parameters. Therefore, inputting the circuit breaker parameters can match the benchmark prediction model with appropriate model parameters, achieving better prediction accuracy.

[0150] S12. Based on the function fitting method, perform function fitting on the single arcing time data set and the single arcing energy data set for the benchmark prediction model, and construct an initial circuit breaker electrical life prediction model in combination with the total arc energy of the circuit breaker;

[0151] The specific function fitting relationship is as follows:

[0152]

[0153] In the formula, represents the single arcing energy obtained through function fitting by the function fitting method, represents the function relationship with the optimal fitting effect.

[0154] The function fitting method refers to polynomial, Fourier function, quadratic Gaussian function, Weibull distribution function, etc.

[0155] In the embodiment of the present invention, a function relationship between the arcing time and the arcing energy is established according to the calculated single arcing time data set and single arcing energy data set. Using the function fitting method, a function fitting function between the single arcing time and the single arcing energy is obtained, and an objective function of the initial circuit breaker electrical life prediction model is constructed in combination with the total arc energy of the circuit breaker.

[0156] It is worth mentioning that is the single arcing energy obtained through function fitting, and the function relationship with the optimal fitting effect is selected as Typically, can be polynomial, Fourier function, quadratic Gaussian function, Weibull distribution function, etc., or can also be obtained by the method of fitting through artificial intelligence algorithms.

[0157] It should be noted that the feasibility of constructing the functional relationship between the single-arc energy and the single-arc time in function fitting is explained. During the process of breaking the rated current, the moment of contact separation is approximately the moment of arc generation, and the arc extinguishes at the current zero-crossing point. The arc current waveform is approximately the same as the load current waveform, but the arc voltage shows a non-linear change. The arc burning time is closely related to the current and voltage waveforms during the arc burning period and the arc starting phase. When the arc starting phase is different, the arc current and voltage waveforms are also significantly different. The waveform of the arc voltage is related to the development of the arc. During the breaking process of the circuit breaker, the development of the arc has obvious stages, and the arc voltage in each stage can be represented by a function, showing a certain pattern. This pattern is reflected in the single-arc energy, that is, there is an obvious non-linear correlation between the single-arc energy and the arc burning time (depending on the arc starting phase).

[0158] S13. Input the preset training operation data set into the initial electrical life prediction model of the circuit breaker for training to generate a training prediction life.

[0159]

[0160] In the formula, represents the training prediction life, and is the training prediction life at the th action, represents the th breaking fitted arc energy, then is the training cumulative arc energy fitted up to the th action.

[0161] In the embodiment of the present invention, the preset training operation data set is input into the initial electrical life prediction model of the circuit breaker for training to generate a training prediction life.

[0162] S14. Determine the standard prediction life by using the single-arc energy data set and the total arc energy of the circuit breaker.

[0163] Further, S14 may include the following sub-steps:

[0164] S141. Input the single-arc energy data set into the preset cumulative arc energy function to generate a cumulative arc energy set;

[0165] The preset cumulative arc energy function is specifically:

[0166]

[0167] In the formula, represents the cumulative arc energy of the circuit breaker after the th action. The cumulative arc energy set is composed of cumulative arc energies, represents the Number of opening operations.

[0168] In the embodiment of the present invention, based on the single-arc energy data set obtained by calculation, a correlation data set between the cumulative arc energy of the circuit breaker and the remaining effective electrical life is obtained. Here, the correlation data set refers to the cumulative arc energy set.

[0169] S142. Use the cumulative arc energy set and the total arc energy of the circuit breaker to input a preset standard prediction life function to determine the standard prediction life.

[0170] It is worth mentioning that, for the convenience of calculation and unified expression, the life of the circuit breaker and the cumulative arc energy are normalized. Based on the obtained cumulative arc energy and the total arc energy of the circuit breaker, if the total life of the circuit breaker is defined as 1, then the relationship between the remaining life of the circuit breaker and the cumulative arc energy at the kth opening can be described by the following preset standard prediction life function:

[0171] The preset standard prediction life function is specifically:

[0172]

[0173] In the formula, represents the standard prediction life of the circuit breaker after the

[0174] In the embodiment of the present invention, the cumulative arc energy set and the total arc energy of the circuit breaker are used to input a preset standard prediction life function for calculation, and then the standard prediction life is output.

[0175] S15. Use the training prediction life and the standard prediction life to determine the average prediction accuracy.

[0176] Further, S15 may include the following sub-steps:

[0177] S151. Use the training prediction life and the standard prediction life to input a preset life prediction accuracy function to generate a life prediction accuracy set.

[0178] The preset life prediction accuracy function is specifically:

[0179]

[0180] In the formula, represents the life prediction accuracy of the circuit breaker after the th operation, and the life prediction accuracy set is composed of

[0181] In the embodiment of the present invention, the accuracy rate of the training prediction life obtained from the initial breaker electrical life prediction model is calculated. The training prediction life and the standard prediction life are input into a preset life prediction accuracy rate function for operation to generate a life prediction accuracy rate set.

[0182] S152. Input the life prediction accuracy rate set into a preset average prediction accuracy rate function to determine the average prediction accuracy rate.

[0183] The preset average prediction accuracy rate function is specifically:

[0184]

[0185] In the formula, represents the average prediction accuracy rate, represents the th action of the breaker's life prediction accuracy rate.

[0186] In the embodiment of the present invention, the life prediction accuracy rate set is input into a preset average prediction accuracy rate function for operation to determine the average prediction accuracy rate.

[0187] S16. When the average prediction accuracy rate is greater than the preset standard prediction accuracy rate, generate a target breaker electrical life prediction model.

[0188] In the embodiment of the present invention, the preset standard prediction accuracy rate is preferably 95%. If the average prediction accuracy rate is greater than 95%, then store the fitting function relationship between the single arcing time and the arcing energy obtained by fitting at this time and its key parameters, and obtain the target breaker electrical life prediction model accordingly.

[0189] Further, after S16, the following steps are also included:

[0190] S17. When the average prediction accuracy rate is less than or equal to the preset standard prediction accuracy rate, then jump to S12.

[0191] Step 206. Use the target breaker electrical life prediction model to predict the life of the breaker to be predicted and generate a life prediction result.

[0192] In the embodiment of the present invention, according to the obtained target breaker electrical life prediction model, the remaining electrical life of the monitoring object (breaker to be predicted) is predicted and output. The storage and calculation of this model can be realized by using a single-chip microcomputer, a host computer, or a digital signal processor, etc. as an execution unit. Only a simple sensor needs to be installed to measure and calculate the arcing time and transmit it to the execution unit to predict the remaining life of the breaker and provide the staff with the real-time operating state information of the breaker.

[0193] It is worth mentioning that the present invention is applicable to various usage scenarios of circuit breakers. When the application scenario or the monitored object is different, the model parameters need to be adjusted in a timely manner. In scenarios with high safety requirements or harsh environments (such as high-temperature environments, humid environments, etc.), the model parameters need to be calibrated.

[0194] It should be noted that the model parameters refer to the parameters of the objective function of the electrical life prediction model of the target circuit breaker, specifically the constant coefficients in the function relationship obtained by fitting (that is, in ).

[0195] Furthermore, based on the function fitting relationship obtained in S12, an electrical life prediction model of the circuit breaker for the cumulative arcing energy is established. Specifically, the function relationship obtained in S12 is used to replace the arcing energy calculation method (preset single arcing energy function) in step 203, that is, the single arcing energy is calculated only through the single arcing time, and the cumulative arcing energy is obtained and the remaining life is predicted. When the circuit breaker operates for the kth time, the predicted remaining electrical life of the circuit breaker is expressed as follows.

[0196] The objective function of the electrical life prediction model of the target circuit breaker is specifically:

[0197]

[0198] In the formula, represents the predicted remaining life at the th operation, represents the target cumulative arcing energy obtained by fitting up to the th operation, represents the current number of opening operations.

[0199] In an embodiment of the present invention, 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. 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. Based on a function fitting method, the single-arc time data set and the single-arc energy data set are fitted to generate a target circuit breaker electrical life prediction model. The life of the circuit breaker to be predicted is predicted through the target circuit breaker electrical life prediction model to generate a life prediction result, which solves the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker, bringing potential safety hazards to the power system. First, by establishing the relationship between the arcing time and the arcing energy during the opening process of the circuit breaker, a target circuit breaker electrical life prediction model is constructed, making the prediction result have high reliability and high accuracy. Second, the present invention avoids massive data storage and calculation, can achieve the effect of fast prediction, and has simple requirements for the data processor. Finally, it can be integrated into the operation and maintenance platform of the transmission and transformation power grid or the digital signal processor. By collecting operation data in real time and inputting it into the target circuit breaker electrical life prediction model, it is used for real-time monitoring of the operation state of the circuit breaker.

[0200] For ease of understanding, a specific application example is provided below:

[0201] The remaining effective electrical life prediction object selected in this application example is a certain high-voltage circuit breaker that can complete the connection and disconnection of a three-phase AC power transmission and transformation system.

[0202] It should be noted that the object of the present invention is a 500 kV circuit breaker device applied to the AC main power grid network. The high-voltage circuit breaker is only a specific object that can be selected.

[0203] Please refer to Figure 5 , Figure 5 which is the flowchart of the effective remaining electrical life prediction method for the high-voltage circuit breaker in the application example of the present invention;

[0204] Step 1: Input the equipment parameters and electrical parameters (basic parameters) of the high voltage in the specific embodiment. The specific parameters include: rated operating voltage 550 kV, rated operating current 8 kA, rated short-circuit breaking current 80 kA, and rated peak withstand current 216 kA.

[0205] Build an electrical life experiment platform, and use 1 voltage differential probe and 1 current probe to collect the arc voltage signal and arc current signal at both ends of the contact during the breaking period of the high-voltage circuit breaker respectively.

[0206] Combined with Figure 5 , the construction process of the relationship between the single-arc energy and the single-arc time is described. The calculation process of the single-arc energy is described, and a period of time before the arcing starting point is selected and recorded as , as can be seen in the figure, the arcing start time point ms, the arcing end time point ms, then the single arcing time in this example is:

[0207]

[0208] The sampling rate of the differential probe used in the embodiment is = 180k, then the sampling interval , and the single arcing energy is:

[0209]

[0210] In this embodiment, it is defined that the allowable wear thickness of the high-voltage contact = 3mm. When the detected reduction in contact thickness reaches 3mm, it is considered that the circuit breaker has failed. At this time, the number of opening operations is 8230. The relationship between the actual single arcing time and the single arcing energy obtained by statistics is as shown in the scatter plot in Figure 3 . It can be seen that there is an obvious correlation between the two. The longer the single arcing time, the greater the arcing energy, and there is a non-linear relationship between the two. When the arcing time is relatively long, the randomness and dispersion of the single arcing energy are also greater.

[0211] Combined with Figure 4 and Figure 5 , it illustrates the construction of the associated data set of the cumulative arcing energy of the circuit breaker and the remaining effective electrical life. It is stipulated that the total electrical life of the high voltage in the embodiment is 1, and its standard predicted life can be calculated by the following formula:

[0212]

[0213] where n = 8230, represents the cumulative arc energy of the sample up to the kth operation, represents the cumulative arc energy at the moment of sample failure, which is also the total arc energy threshold for reliable operation of the sample, The calculation method of is referenced to the preset single arcing energy function. The relationship between the cumulative arc energy and the remaining electrical life can be obtained as shown by the solid line in Figure 4 .

[0214] Based on Figure 3 the data set of the actual single arcing time and the single arcing energy shown in, establish the functional relationship between the arcing time and the arcing energy. Use the obtained functional relationship to calculate the single predicted arcing energy , and replace in the above formula to calculate and predict the remaining electrical life, and continuously iterate and update the function parameters until the predicted average accuracy reaches 95%.

[0215] 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:

[0216] The relational expression obtained by quadratic polynomial fitting is:

[0217]

[0218] where, is the single-arc energy predicted by using the quadratic polynomial, is the actually measured single-arc time, are the function coefficients, and the optimal coefficient solution is , and the predicted average accuracy is 96%.

[0219] The relational expression obtained by exponential function fitting is:

[0220]

[0221] where, is the single-arc energy predicted by using the exponential function, is the actually measured single-arc time, are the function coefficients, and the optimal coefficient solution is , and the predicted average accuracy is 93.5%.

[0222] The relational expression obtained by Weibull function fitting is:

[0223]

[0224] where, is the single-arc energy predicted by using the Weibull function, is the actually measured single-arc time, are the function coefficients, and the optimal coefficient solution is , and the predicted average accuracy is 97.9%.

[0225] In this application example, the model obtained by using Weibull function fitting has the highest predicted average accuracy. The obtained fitting curve is as shown by the Figure 3 solid line. The relationship between the predicted electrical life and the cumulative arcing energy can be expressed by the following formula, and the prediction result is as shown by the Figure 4 dashed line in.

[0226]

[0227] It should be noted that the functional relationship and function coefficients selected in this example are not the only methods. In the actual application process, the function type and function coefficients need to be adjusted according to the actual measurement results, and the functional relationship with the smallest calculation amount should be selected as the basis of the final prediction model while ensuring the prediction accuracy.

[0228] The following describes the application of the obtained prediction model in actual situations. The objective function of the obtained target breaker electrical life prediction model uses a digital signal processor as the storage and calculation unit. The model calculation code (the calculation of the objective function), the total arcing energy = 1.38×105, and the safety allowable range are input into the digital signal processor. A high-voltage of the same model is selected as the test sample, and an acceleration sensor is installed at the moving contact part of the test sample. Based on the change in acceleration, the start time and end time of each action of the test sample are detected and recorded. 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 therefrom, accumulates and stores it, and simultaneously calculates the predicted remaining life , and the prediction result is output to the outside through a display screen. When the cumulative arcing energy value exceeds the safety threshold , the digital signal processor issues an alarm signal, which is displayed on the display screen to remind the staff to perform maintenance and repair. To verify the accuracy of the model, the test sample continues to operate. When it operates 8036 times, the predicted end of life is obtained. Actually, when it operates 8515 times, the contact wear amount reaches the safety allowable value of 3 mm. The prediction accuracy rate reaches 94%.

[0229] The method of using the prediction model adopted by the test sample in this embodiment is not unique. In the test sample of the embodiment, the arcing time is obtained by using a sensor to detect the acceleration change of the moving contact. In actual applications, other methods can also be used to obtain the arcing time, such as the transient current method, intelligent detection instrument detection, etc. In the test sample of the embodiment, a digital signal processor is selected as the storage and calculation unit. In actual applications, according to needs, other tools that can achieve the required functions, such as single-chip microcomputers and upper computers, can be selected. The safety threshold set in the test sample of the embodiment , and in actual applications, the safety threshold is adjusted according to the safety requirements of the application scenario. In occasions with higher reliability requirements for the breaker, the safety threshold should be set lower.

[0230] In the actual application process, the model parameter values and the allowable contact wear thickness need to be corrected according to the specific breaker type, specific product model, and specific application scenario to improve the adaptability of a method for predicting the effective remaining electrical life of a high-voltage breaker of the present invention. It can be understood that this method has a certain portability and can also play a role when the object and usage scenario are changed. Therefore, it should be regarded as belonging to the protection scope of the present invention.

[0231] It should be further noted that the present invention is easily integrated into the power network operation and maintenance platform of the main power grid system. Moreover, the method can not only independently implement the function of predicting the effective remaining life of a certain circuit breaker, but also centrally monitor and predict the life of all circuit breakers within a certain area. If the method disclosed in this invention patent application can be successfully applied, it will be beneficial to reduce the repair rate of electrical appliance failures and improve the operation reliability of the power system.

[0232] Please refer to Figure 6 , Figure 6 which is the structural block diagram of an effective remaining electrical life prediction system for a high-voltage circuit breaker provided in Embodiment 3 of the present invention.

[0233] An effective remaining electrical life prediction system for a high-voltage circuit breaker provided by the present invention includes:

[0234] A response module 301, configured to, in response to a life test request for a test circuit breaker, obtain in real time a test operation data set associated with the test circuit breaker;

[0235] A single arcing operation module 302, configured to input the test operation data set into a preset single arcing function to generate a single arcing time data set and a single arcing energy data set;

[0236] A total arcing energy module 303 of the circuit breaker, configured to input the single arcing energy data set into a preset total arcing energy function of the circuit breaker to generate the total arcing energy of the circuit breaker.

[0237] 304, configured to perform function fitting on the single arcing time data set and the energy data set of the single arcing function based on the function fitting method to generate a target circuit breaker electrical life prediction model;

[0238] A life prediction module 305, 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.

[0239] Further, the test operation data set includes arc voltage data at both ends of the contacts during the operation of the circuit breaker, arc current data between the contacts, arcing start time data, and arc extinction time data;

[0240] Among them, the arcing start time data and the arc extinction time data are determined by the mechanical factor measurement method or the transient current method.

[0241] Further, the preset single arcing function includes a single arcing time function and a single arcing energy function, and the single arcing operation module 302 includes:

[0242] The single arcing time data set sub-module is used to input the arcing start time data and the arcing extinction time data into the single arcing time function to generate a single arcing time data set;

[0243] The single arcing time function is specifically as follows:

[0244]

[0245] In the formula, represents the th single arcing time data, where , represents the number of breaking operations completed. The single arcing time data set consists of single arcing time data, represents the arcing start time data at the th operation, represents the arcing extinction time data at the th operation;

[0246] The single arcing energy data set sub-module is used to input the arcing start time data, the arcing extinction time data, the arc voltage data at both ends, and the arc current data between the contacts into the single arcing energy function to generate a single arcing energy data set;

[0247] The single arcing energy function is specifically as follows:

[0248]

[0249] In the formula, represents the th single arcing energy data. The single arcing energy data set consists of single arcing energy data, represents the arc voltage data at both ends at the th operation moment, represents the arc current data between the contacts at the th operation moment, represents the sampling interval.

[0250] Furthermore, the preset total arc energy function of the circuit breaker is specifically as follows:

[0251]

[0252] In the formula, represents the total arc energy of the circuit breaker, represents the number of breaking operations completed.

[0253] Furthermore, the function fitting module 304 includes:

[0254] A reference prediction model sub-module, which is used to obtain the basic parameters associated with the test circuit breaker, input the basic parameters into the preset circuit breaker reference prediction model platform for matching, and obtain a reference prediction model;

[0255] An initial circuit breaker electrical life prediction model sub-module, which is used to perform function fitting on the reference prediction model based on the single arcing time data set and the single arcing energy data set by using the function fitting method, and construct an initial circuit breaker electrical life prediction model in combination with the total arc energy of the circuit breaker;

[0256] The specific function fitting relationship is:

[0257]

[0258] In the formula, represents the single arcing energy obtained by function fitting through the function fitting method, represents the function relationship with the optimal fitting effect;

[0259] A training prediction life sub-module, which is used to input the preset training operation data set into the initial circuit breaker electrical life prediction model for training to generate a training prediction life;

[0260] A standard prediction life sub-module, which is used to determine the standard prediction life by using the single arcing energy data set and the total arc energy of the circuit breaker;

[0261] An average prediction accuracy sub-module, which is used to determine the average prediction accuracy by using the training prediction life and the standard prediction life;

[0262] A target circuit breaker electrical life prediction model sub-module, which is used to generate a target circuit breaker electrical life prediction model when the average prediction accuracy is greater than the preset standard prediction accuracy.

[0263] Furthermore, the objective function of the target circuit breaker electrical life prediction model is specifically:

[0264]

[0265] In the formula, represents the predicted remaining life at the th action, represents the target cumulative arcing energy obtained by fitting up to the th action, represents the current number of opening operations.

[0266] Furthermore, the standard prediction life sub-module includes:

[0267] An accumulated arcing energy set unit, which is used to input the single arcing energy data set into the preset accumulated arcing energy function to generate an accumulated arcing energy set;

[0268] The preset cumulative arcing energy function is specifically as follows:

[0269]

[0270] In the formula, represents the cumulative arcing energy of the circuit breaker after the -th operation. The cumulative arcing energy set is composed of cumulative arcing energies, represents the -th opening operation times;

[0271] The standard predicted life calculation unit is used to input the cumulative arcing energy set and the total arc energy of the circuit breaker into the preset standard predicted life function to determine the standard predicted life;

[0272] The preset standard predicted life function is specifically as follows:

[0273]

[0274] In the formula, represents the standard predicted life of the circuit breaker after the -th operation.

[0275] Furthermore, the average prediction accuracy sub-module includes:

[0276] The life prediction accuracy set unit is used to input the training predicted life and the standard predicted life into the preset life prediction accuracy function to generate the life prediction accuracy set;

[0277] The preset life prediction accuracy function is specifically as follows:

[0278]

[0279] In the formula, represents the life prediction accuracy of the circuit breaker after the -th operation. The life prediction accuracy set is composed of life prediction accuracies;

[0280] The average prediction accuracy calculation unit is used to input the life prediction accuracy set into the preset average prediction accuracy function to determine the average prediction accuracy;

[0281] The preset average prediction accuracy function is specifically as follows:

[0282]

[0283] In the formula, represents the average prediction accuracy, represents the Accuracy of the life prediction of the circuit breaker after the next operation.

[0284] In an embodiment of the present invention, in response to a life test request for a test circuit breaker, a test operation data set associated with the test circuit breaker is obtained 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. Based on a function fitting method, the single-arc time data set and the single-arc energy data set are function-fitted to generate a target circuit breaker electrical life prediction model. The life of the circuit breaker to be predicted is predicted through the target circuit breaker electrical life prediction model to generate a life prediction result, which solves the technical problem that the existing circuit breaker life prediction method cannot accurately and quickly detect the life of the circuit breaker, bringing potential safety hazards to the power system. First, by establishing the relationship between the arcing time and the arcing energy during the opening process of the circuit breaker, a target circuit breaker electrical life prediction model is constructed, making the prediction result have high reliability and high accuracy. Second, the present invention avoids massive data storage and calculation, can achieve the effect of rapid prediction, and has simple requirements for the data processor. Finally, it can be integrated into the operation and maintenance platform of the transmission and transformation power grid or a digital signal processor, and the operation data is collected in real time and input into the target circuit breaker electrical life prediction model for real-time monitoring of the operation state of the circuit breaker.

[0285] Please refer to Figure 7 , Figure 7 which shows a structural block diagram of a computer device according to an embodiment of the present invention.

[0286] An electronic device according to an embodiment of the present invention, the electronic device includes: a memory 401 and a processor 402, and a computer program is stored in the memory 402; when the computer program is executed by the processor 402, the processor 402 is caused to execute the effective remaining electrical life prediction method of the high-voltage circuit breaker according to any of the above embodiments.

[0287] The memory 401 may 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 code 413 for executing any method steps in the above-described methods. For example, the storage space 403 for the program code may include respective program codes 413 for implementing various steps in the above methods. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed in a suitable form, for example. When these codes are run by a computing processing device, the computing processing device is caused to execute the respective steps in the methods described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed in a suitable form, for example. When these codes are run by a computing processing device, the computing processing device is caused to execute the respective steps in the DC charging pile control method described above.

[0288] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the effective remaining electrical life prediction method of the high-voltage circuit breaker as in any of the above embodiments.

[0289] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0290] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other may be through some interfaces, indirect couplings or communication connections of devices or units, and may be electrical, mechanical, or other forms.

[0291] The unit described as a separation component may or may not be physically separated, and the component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0292] In addition, each functional unit in various embodiments of the present invention may be integrated in a processing unit, may exist separately as individual physical units, or two or more units may be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0293] 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 solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, 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 may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0294] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. An effective remaining electrical life prediction method for a high-voltage circuit breaker, characterized in that, Including: In response to a life test request for a test circuit breaker, obtaining in real time a test operation data set associated with the test circuit breaker; Using the test operation data set to input a preset single arcing function to generate a single arcing time data set and a single arcing energy data set; Using the single arcing energy data set to input a preset total arcing energy function of the circuit breaker to generate the total arcing energy of the circuit breaker; Performing function fitting on the single arcing time data set and the single arcing energy data set, and constructing a target circuit breaker electrical life prediction model in combination with the total arcing energy of the circuit breaker; Performing life prediction on the circuit breaker to be predicted through the target circuit breaker electrical life prediction model to generate a life prediction result; The step of performing function fitting on the single arcing time data set and the single arcing energy data set, and constructing a target circuit breaker electrical life prediction model in combination with the total arcing energy of the circuit breaker includes: Obtaining basic parameters associated with the test circuit breaker, and inputting the basic parameters into a preset circuit breaker benchmark prediction model platform for matching to obtain a benchmark prediction model; Based on the function fitting method, performing function fitting on the single arcing time data set and the single arcing energy data set on the benchmark prediction model, and constructing an initial circuit breaker electrical life prediction model in combination with the total arcing energy of the circuit breaker; The specific function fitting relationship is: ΔE predi = f(t arci ) where ΔE predi represents the single-arc ignition energy obtained by function fitting through the function fitting method, and f(t arci ) represents the function relationship with the optimal fitting effect; Using a preset training operation data set to input the initial circuit breaker electrical life prediction model for training to generate a training predicted life; Using the single arcing energy data set and the total arcing energy of the circuit breaker to determine a standard predicted life; Using the training predicted life and the standard predicted life to determine an average prediction accuracy rate; When the average prediction accuracy rate is greater than a preset standard prediction accuracy rate, generating a target circuit breaker electrical life prediction model.

2. The effective remaining electrical life prediction method of the high-voltage circuit breaker according to claim 1, characterized in that The test operation data set includes arc voltage data at both ends of the contacts during the operation of the circuit breaker, arc current data between the contacts, arcing start time data, and arc extinction time data; Among them, the arcing start time data and the arc extinction time data are determined by a mechanical factor measurement method or a transient current method.

3. The effective remaining electrical life prediction method for a high-voltage circuit breaker according to claim 2, characterized in that, The preset single arcing function includes a single arcing time function and a single arcing energy function. The step of using the test operation data set to input the preset single arcing function to generate a single arcing time data set and a single arcing energy data set includes: Using the arcing start time data and the arc extinction time data to input the single arcing time function to generate a single arcing time data set; The specific single arcing time function is: t arci = t 2i - t 1i where t arci represents the i-th single arcing time data, where i = 1, 2, ..., n, and n represents the number of opening operations completed. The single arcing time data set is composed of n pieces of the single arcing time data, and t 1i represents the arcing start time data at the i-th operation, and t 2i represents the arcing extinction time data at the i-th operation; Using the arcing start time data, the arc extinction time data, the arc voltage data at both ends, and the arc current data between the contacts to input the single arcing energy function to generate a single arcing energy data set; The specific single arcing energy function is: In the formula, ΔE arci represents the i-th single arcing energy data, and the single arcing energy data set is composed of n pieces of the single arcing energy data. U i (t) represents the two-terminal arc voltage data at the t-th moment of the i-th action, and I i (t) represents the arc current data between the contacts at the t-th moment of the i-th action, and t represents the sampling interval.

4. The effective remaining electrical life prediction method of the high-voltage circuit breaker according to claim 1, characterized in that, The specific preset total arcing energy function of the circuit breaker is: Where, E pe represents the total arc energy of the circuit breaker, and n represents the number of opening operations completed.

5. The effective remaining electrical life prediction method of the high-voltage circuit breaker according to claim 1, characterized in that The objective function of the target circuit breaker electrical life prediction model is specifically: where r predk represents the predicted remaining life at the k-th operation, represents the target cumulative arcing energy obtained by fitting up to the i-th operation, and k represents the current number of opening operations.

6. The effective remaining electrical life prediction method for the high-voltage circuit breaker according to claim 1, characterized in that The step of using the single arcing energy data set and the total arcing energy of the circuit breaker to determine a standard predicted life includes: Input the single-arc energy dataset into a preset cumulative arc energy function to generate a cumulative arc energy set; The specific form of the preset cumulative arc energy function is: where E k represents the cumulative arcing energy of the circuit breaker after the k-th operation, and the set of the cumulative arcing energy is composed of k pieces of the cumulative arcing energy, and k represents the number of the k-th opening operation; 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; The specific form of the preset standard predicted life function is: where r k represents the standard predicted life of the circuit breaker after the k-th operation.

7. The effective remaining electrical life prediction method of the high-voltage circuit breaker according to claim 1, characterized in that The step of determining the average prediction accuracy by using the training predicted life and the standard predicted life includes: Input the training predicted life and the standard predicted life into a preset life prediction accuracy function to generate a life prediction accuracy set; The specific form of the preset life prediction accuracy function is: where α k represents the life prediction accuracy of the circuit breaker after the k-th operation, and the life prediction accuracy set is composed of k such life prediction accuracies; Input the life prediction accuracy set into a preset average prediction accuracy function to determine the average prediction accuracy; The specific form of the preset average prediction accuracy function is: Where α represents the average prediction accuracy, and α i represents the life prediction accuracy of the circuit breaker after the i-th operation.

8. An effective remaining electrical life prediction system for a high-voltage circuit breaker, characterized in that, It includes: A response module for, in response to a life test request for a test circuit breaker, obtaining in real time the test operation dataset associated with the test circuit breaker; A single-arc operation module for inputting the test operation dataset into a preset single-arc function to generate a single-arc time dataset and a single-arc energy dataset; A circuit breaker total arc energy module for inputting the single-arc energy dataset into a preset circuit breaker total arc energy function to generate the circuit breaker total arc energy; A function fitting module for, based on the function fitting method, performing function fitting on the single-arc time dataset and the single-arc energy dataset to generate a target circuit breaker electrical life prediction model; A life prediction module for predicting the life of a circuit breaker to be predicted through the target circuit breaker electrical life prediction model to generate a life prediction result; The function fitting module includes: A reference prediction model sub-module for obtaining the 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; An initial circuit breaker electrical life prediction model sub-module for, based on the function fitting method, performing function fitting on the reference prediction model with the single-arc time dataset and the single-arc energy dataset and constructing an initial circuit breaker electrical life prediction model in combination with the circuit breaker total arc energy; The specific form of the function fitting relationship is: ΔE predi = f(t arci ) where ΔE predi represents the single arcing energy obtained by function fitting through the function fitting method, and f(t arci ) represents the function relationship with the optimal fitting effect; A training predicted life sub-module for inputting a preset training operation dataset into the initial circuit breaker electrical life prediction model for training to generate a training predicted life; A standard predicted life sub-module for determining the standard predicted life by using the single-arc energy dataset and the circuit breaker total arc energy; An average prediction accuracy sub-module for determining the average prediction accuracy by using the training predicted life and the standard predicted life; A target circuit breaker electrical life prediction model sub-module for, when the average prediction accuracy is greater than the preset standard prediction accuracy, generating a target circuit breaker electrical life prediction model.

9. An electronic device, characterized in that, It includes a memory and a processor. When a computer program stored in the memory is executed by the processor, the processor executes the steps of the method for predicting the effective remaining electrical life of a high-voltage circuit breaker according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the effective remaining electrical life prediction method for the high-voltage circuit breaker according to any one of claims 1-7.

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