Fault diagnosis method and device for motor GIS disconnecting switch

Abstract

The invention provides a fault diagnosis method and device for a motor GIS isolation switch. The method comprises the steps that firstly, a power curve in the operation process of a motor is obtained, the power curve is preprocessed, a first target curve is obtained, and preprocessing at least comprises abnormal value filtering and missing value complementing; calculating a correlation coefficient based on the first target curve through a hill climbing algorithm to obtain a target coefficient; and finally, comparing the target coefficient with a first threshold value to determine whether the isolating switch of the motor has a fault or not. According to the method, the power curve is drawn based on the current and the voltage of the motor, and correlation judgment is performed according to the power curve optimized by the hill climbing algorithm, so that the interference of different periods of the power curve is avoided, and the problem of relatively low fault judgment accuracy of mechanism jamming and mechanism not-in-place in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of motor diagnosis, and in particular to a fault diagnosis method for a motor GIS isolating switch, a fault diagnosis device for a motor GIS isolating switch, a computer-readable storage medium and a motor. Background Art

[0002] Disconnectors are important equipment for changing the operation mode of power grids. However, due to the fully enclosed characteristics of GIS disconnectors, the status of primary equipment cannot be visually viewed during daily maintenance. Currently, the main method for confirming the position of disconnectors relies solely on opening and closing signs, connecting rod markings, travel switches, etc. There is no quantitative judgment on the status of the disconnector, and it is impossible to judge problems such as mechanism jamming.

[0003] After searching the existing technical documents, it was found that the Chinese patent application number is: CN202011491841.9, and the name is a GIS disconnector fault diagnosis method based on multiple feature quantities. The invention uses the GIS disconnector motor current, spindle angle and image information as feature quantities for fault judgment, but the invention only simply sets thresholds for the average value and extreme value of each feature quantity to make judgments, which makes it difficult to identify minor jamming faults. Further analysis and identification of the fault characteristics of the GIS disconnector is required. Therefore, the accuracy of the judgment of mechanism jamming and mechanism insufficiency in the prior art is low. Summary of the invention

[0004] The main purpose of the present application is to provide a fault diagnosis method for a motor GIS isolating switch, a fault diagnosis device for a motor GIS isolating switch, a computer-readable storage medium and a motor, so as to at least solve the problem of low accuracy in judging the faults of mechanism jamming and mechanism not being in place in the prior art.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a fault diagnosis method for a motor GIS disconnector is provided, comprising: obtaining a power curve during the operation of the motor, and preprocessing the power curve to obtain a first target curve, wherein the preprocessing at least includes outlier filtering and missing value completion; calculating a correlation coefficient based on the first target curve by a hill climbing algorithm to obtain a target coefficient; and comparing the target coefficient with a first threshold to determine whether the disconnector of the motor is faulty.

[0006] Obtaining a power curve during the operation of the motor, including: monitoring the voltage of the motor in real time through a voltage sensor to obtain a second target curve; monitoring the voltage of the motor in real time through a current sensor to obtain a third target curve; and calculating based on the second target curve and the third target curve to obtain the power curve during the operation of the motor.

[0007] Optionally, the power curve is preprocessed, including: traversing the power curve, and when any sampling point value is less than a second threshold, determining the sampling point as a first target sample point; when any sampling point value is greater than or equal to the average of other sampling points in the power curve, determining the sampling point as the first target sample point; and deleting the first target sample point in the power curve to complete outlier filtering of the power curve.

[0008] Optionally, preprocessing the power curve to obtain the first target curve further includes: traversing the power curve to determine missing sampling points in the power curve as second target sampling points; and completing the second target sampling points based on linear interpolation to obtain the first target curve.

[0009] Optionally, calculating the correlation coefficient based on the first target curve by a hill climbing algorithm to obtain a target coefficient includes: randomly intercepting the first target curve based on a first preset step size to obtain a second target curve P 1 =[p 11 ,p 12 ,…,p n1 ] and P 2 =[p 21 ,p 22 ,…,p 2n ]; Substitute the second target curve into the first preset formula Based on the hill climbing algorithm, the second target power curve P 2 =[p 21 ,p 22 ,…,p 2n ] is optimized so that R(P 1 ,P 2 ) obtains the maximum value and obtains the target coefficient, where E is the mathematical expectation value.

[0010] Optionally, the second target power curve P is calculated based on a hill climbing algorithm. 2 =[p 21 ,p 22 ,…,p 2n ] is optimized so that R(P 1 ,P 2 ) to obtain the maximum value, and obtain the target coefficient, including: according to the second target power curve P 1 =[p 11 ,p 12 ,…,p 1n ] and P 2 =[p 21 ,p 22 ,…,p 2n ], set the objective function N is a natural number; the independent variable x takes an arbitrary value as the current solution, and constructs a neighborhood set based on the initial solution and the second preset step size; based on the samples in the neighborhood set, the objective function is substituted, and the independent variable x that makes the objective function reach the maximum value is determined as the optimal solution of the current neighborhood set; the neighborhood set is updated with the optimal solution as the current solution, and the optimal solution is updated based on the updated neighborhood set until the optimal solutions are the same in two consecutive updating processes or the number of updates reaches the maximum number, thereby obtaining the target solution; the target solution is substituted into the first preset formula to obtain the target coefficient.

[0011] Optionally, a comparison is performed based on the target coefficient and a first threshold value to determine whether the isolating switch of the motor is faulty, including: when the minimum value of the target coefficient is greater than or equal to the first threshold value, determining that the isolating switch of the motor is not faulty; when the minimum value of the target coefficient is less than the first threshold value, determining that the isolating switch of the motor is faulty.

[0012] According to another aspect of the present application, a fault diagnosis device for a motor GIS disconnector is provided, the device comprising: an acquisition unit, for acquiring a power curve during the operation of the motor, and preprocessing the power curve to obtain a first target curve, wherein the preprocessing at least includes outlier filtering and missing value completion; a calculation unit, for calculating a correlation coefficient based on the first target curve by a hill climbing algorithm to obtain a target coefficient; and a determination unit, for comparing the target coefficient with a first threshold to determine whether the disconnector of the motor is faulty.

[0013] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0014] According to another aspect of the present application, a motor is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of the described methods.

[0015] Applying the technical solution of the present application, firstly, the power curve during the operation of the motor is obtained, and the power curve is preprocessed to obtain a first target curve, wherein the preprocessing includes at least outlier filtering and missing value completion; then, the correlation coefficient is calculated based on the first target curve through a hill climbing algorithm to obtain a target coefficient; finally, the target coefficient is compared with the first threshold value to determine whether the isolating switch of the motor is faulty. The present application draws a power curve based on the current and voltage of the motor, and makes a correlation judgment based on the power curve optimized by the hill climbing algorithm. Compared with the threshold judgment based on the average value of characteristic quantities such as motor current, spindle angle and image information in the prior art, the present application makes a judgment based on the correlation coefficient, thereby avoiding interference from different periods of the power curve and solving the problem of low accuracy in judging the failure of the mechanism being blocked or not in place in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A hardware structure block diagram of a mobile terminal for fault diagnosis of a motor GIS isolating switch provided in an embodiment of the present application is shown;

[0017] Figure 2 A schematic flow chart of a fault diagnosis method for a motor GIS isolating switch provided according to an embodiment of the present application is shown;

[0018] Figure 3 A power curve diagram of a normal isolating switch provided according to an embodiment of the present application is shown;

[0019] Figure 4 A power curve diagram of a slightly stuck isolating switch provided according to an embodiment of the present application is shown;

[0020] Figure 5 A structural block diagram of a fault diagnosis device for a motor GIS disconnect switch provided according to an embodiment of the present application is shown.

[0021] The above drawings include the following reference numerals:

[0022] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0023] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0024] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] As introduced in the background technology, in the prior art, threshold judgment is performed through the average values ​​of characteristic quantities such as motor current, spindle angle and image information. In order to solve the problem of low accuracy in judging mechanism jamming and mechanism out of place faults, the embodiments of the present application provide a fault diagnosis method for a motor GIS isolating switch, a fault diagnosis device for a motor GIS isolating switch, a computer-readable storage medium and a motor.

[0027] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0028] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 1 is a hardware structure block diagram of a mobile terminal of a fault diagnosis method for a motor GIS isolating switch according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0029] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the display method of device information in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0030] In this embodiment, a fault diagnosis method for a motor GIS disconnector running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] Figure 2 FIG. 1 is a flow chart of a fault diagnosis method for a motor GIS isolating switch according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0032] Step S201, obtaining a power curve during the operation of the motor, and preprocessing the power curve to obtain a first target curve, wherein the preprocessing at least includes outlier filtering and missing value completion;

[0033] Specifically, during the operation of the motor, the power data of the motor is collected in real time through the corresponding sensors or monitoring systems. These data are usually in the form of time series, that is, the curve of power changing over time. The power curve data is preprocessed, that is, for the power curve, if there is a sampling point value that is negative or greater than 10 times the average value of all elements in the set, it is identified as abnormal data. For missing data and identified abnormal data values, linear interpolation is used to fill in.

[0034] Step S202, calculating the correlation coefficient by a hill climbing algorithm based on the first target curve to obtain a target coefficient;

[0035] Specifically, the hill climbing algorithm is a local search algorithm used to find the optimal solution in a given data set. In this step, the hill climbing algorithm is used to analyze the first target curve after preprocessing and calculate one or more correlation coefficients. These coefficients may represent the similarity between different parts of the curve, the continuity of the change trend, or other characteristics related to the state of the disconnector. After processing by the hill climbing algorithm, one or more target coefficients will be obtained, which will serve as the basis for subsequent fault judgment.

[0036] Step S203: Compare the target coefficient with the first threshold value to determine whether the isolating switch of the motor fails.

[0037] Specifically, one or more first thresholds are set according to historical data, empirical knowledge or industry standards, and these thresholds are used to define the boundary between the normal working state and the fault state of the isolating switch.

[0038] It can be seen that the embodiment of the present application provides a fault diagnosis method for a motor GIS isolating switch, which obtains and analyzes the power curve during the operation of the motor, calculates the correlation coefficient using a hill climbing algorithm, and compares it with a preset threshold value, thereby achieving effective diagnosis of the motor GIS isolating switch fault. This method has the advantages of real-time performance and high degree of automation, and helps to improve the efficiency and accuracy of equipment maintenance.

[0039] As a possible implementation method, the power curve during the operation of the motor is obtained, including: monitoring the voltage of the motor in real time through a voltage sensor to obtain a second target curve; monitoring the voltage of the motor in real time through a current sensor to obtain a third target curve; and calculating based on the second target curve and the third target curve to obtain the power curve during the operation of the motor.

[0040] Specifically, the voltage and current of the motor are collected through a voltage sensor and a current sensor, and the real-time voltage value and current value are multiplied to obtain a power curve during the operation of the motor.

[0041] As a possible implementation method, preprocessing the power curve includes the following steps:

[0042] Step 301, traversing the power curve, when any sampling point value is less than a second threshold, determining the sampling point as a first target sampling point;

[0043] Specifically, the system checks each sampling point in the power curve in turn, and each sampling point represents a power value at a certain moment. The second threshold is usually set based on experience or historical data to distinguish between a normal operating state and an abnormal state.

[0044] Step 302, when the value of any sampling point is greater than or equal to the average of other sampling points in the power curve, determine the sampling point as the first target sampling point;

[0045] Specifically, while determining the first target sample point, the mean of all sampling points in the power curve except the first target sample point is calculated. For each sampling point, if its value is greater than or equal to the above-calculated mean, the sampling point is determined as the first target sample point. This step is mainly to screen out those sampling points that are obviously deviated from the normal operating state.

[0046] Step 303: Delete the first target sample point in the power curve to complete outlier filtering of the power curve.

[0047] Specifically, all data points in the power curve marked as the first target sample points are deleted, which helps to eliminate abnormal fluctuations in the power curve and ensure the basic data quality for subsequent analysis.

[0048] In summary, in the preprocessing stage of the motor GIS disconnector fault diagnosis method, the system can effectively preprocess the power curve, remove abnormal values, and retain data reflecting the normal operation of the motor. This not only improves the accuracy of fault diagnosis, but also ensures the reliability and stability of the analysis results. So that subsequent analysis can accurately reflect the operating status of the motor.

[0049] As a possible implementation method, preprocessing the power curve to obtain the first target curve also includes: traversing the power curve to determine the missing sampling points in the power curve as second target sampling points; and completing the second target sampling points based on linear interpolation to obtain the first target curve.

[0050] Specifically, linear interpolation is a simple and effective interpolation method that assumes that the data change between two known data points is linear. Through the above steps, the system can effectively pre-process the power curve, fill in the missing sampling points, and ensure the integrity of the power curve.

[0051] As a possible implementation method, the correlation coefficient is calculated based on the first target curve by using a hill climbing algorithm to obtain a target coefficient, including:

[0052] The first target curve is randomly intercepted based on the first preset step length to obtain the second target curve P 1 =[p 11 ,p 12 ,…,p 1n ] and P 2 =[p 21 ,p 22 ,…,p 2n ];

[0053] Specifically, a random starting point is selected, and a data segment having a length of a first preset step length is intercepted to form a second target curve. This step ensures that the intercepted data segment can reflect the running state of the motor and has a certain degree of randomness.

[0054] Substitute the second target curve into the first preset formula Based on the hill climbing algorithm, the second target power curve P 2 =[p 21 ,p 22 ,…,p 2n ] is optimized so that R(P 1 ,P 2 ) to obtain the maximum value and obtain the target coefficient, where E is the mathematical expectation value.

[0055] Through the above steps, the system can calculate the correlation coefficient based on the first target curve through the hill climbing algorithm to obtain the target coefficient. This process not only improves the accuracy of fault diagnosis, but also ensures the reliability and stability of the analysis results.

[0056] As a possible implementation method, the second target power curve P is calculated based on the hill climbing algorithm. 2 =[p 21 ,p 22 ,…,p 2n ] is optimized so that R(P 1 ,P 2 ) to obtain the maximum value and obtain the target coefficient, including the following steps:

[0057] Step 401: According to the second target power curve P 1 =[p 11 ,p 12 ,…,p 1n ] and P 2 =[p 21 ,p 22 ,…,p 2n ], set the objective function N is a natural number;

[0058] Step 402, taking an arbitrary value of the independent variable x as the current solution, and constructing a neighborhood set based on the initial solution and the second preset step size;

[0059] Specifically, the initial solution x=0 can be selected; the neighborhood set N(x)=[xm,x-m+1,…,x+m] is selected, where m is a set neighborhood range parameter, and m=10 is usually taken in the specific implementation of the invention.

[0060] Step 403, substituting the samples in the neighborhood set into the objective function, and determining the independent variable x that makes the objective function obtain the maximum value as the optimal solution of the current neighborhood set;

[0061] Specifically, the optimal solution is selected, and the solution that maximizes the objective function is selected from the neighborhood set:

[0062] Step 404, using the optimal solution as the current solution to update the neighborhood set and updating the optimal solution based on the updated neighborhood set until the optimal solution is the same in two consecutive update processes or the number of updates reaches a maximum number, thereby obtaining the target solution;

[0063] Step 405, substituting the target solution into the first preset formula to obtain the target coefficient.

[0064] Specifically, the neighborhood set N(x') and the optimal solution calculation are repeatedly updated until the optimal solution is found as E(P 1 P 2 ), then the correlation coefficient can be calculated The basis for judging the failure of the isolating switch is as follows: for any power curve P, the qualified standard is minR(P,P i )≥0.95, where Pi is any historical comparison power curve set or phase-to-phase comparison power curve set.

[0065] Through the above steps, the system can optimize the second target power curve based on the hill climbing algorithm so that its correlation with the reference data reaches the maximum value, thereby obtaining the target coefficient. This process not only improves the accuracy of fault diagnosis, but also ensures the reliability and stability of the analysis results.

[0066] As a possible implementation method, a comparison is made between the target coefficient and the first threshold to determine whether the isolating switch of the motor is faulty, including: when the minimum value of the target coefficient is greater than or equal to the first threshold, determining that the isolating switch of the motor is not faulty; when the minimum value of the target coefficient is less than the first threshold, determining that the isolating switch of the motor is faulty.

[0067] Through the above steps, the system can accurately determine whether the isolating switch of the motor is faulty based on the comparison between the target coefficient and the first threshold value.

[0068] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the fault diagnosis method of the motor GIS disconnector of the present application will be described in detail below in combination with specific embodiments.

[0069] This embodiment relates to a specific fault diagnosis method for a motor GIS disconnector. In the specific implementation of the invention, a normal disconnector and a slightly blocked disconnector are taken as examples, and the motor voltage and current of the two disconnectors are collected for the last three times of opening. The data sampling interval is 1ms, and the power curve is calculated. Figure 3 This is the power curve of a normal isolating switch. Figure 4 It is the power curve diagram of the isolating switch with slight jamming, ABC is the phase A, phase B and phase C of the circuit, and the comparison of the fault diagnosis results of a typical normal isolating switch and a isolating switch with slight jamming is shown in Table 1.

[0070] Table 1

[0071]

[0072] It can be seen from the results that the method of the present invention can accurately determine that the correlation coefficient between the power curves of the AC phase and the AB phase is low, thereby determining that there is a defect in phase A. At the same time, by comparing the calculation results without hill climbing algorithm optimization with the calculation results of the method of the present invention, it can be seen that the correlation coefficients of the power curves of the typical normal disconnector and the fault disconnector after optimization are significantly different, which is convenient for comparison, while the correlation coefficient before optimization is easily disturbed, resulting in the inability to determine the fault situation.

[0073] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0074] The embodiment of the present application also provides a fault diagnosis device for a motor GIS isolating switch. It should be noted that the fault diagnosis device for a motor GIS isolating switch in the embodiment of the present application can be used to execute the fault diagnosis method for a motor GIS isolating switch provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0075] The following is an introduction to the fault diagnosis device for the motor GIS isolating switch provided in an embodiment of the present application.

[0076] Figure 5 1 is a structural block diagram of a fault diagnosis device for a motor GIS disconnector according to an embodiment of the present application. Figure 5 As shown, the device includes: an acquisition unit 10, a calculation unit 20 and a determination unit 30.

[0077] An acquisition unit 10 is used to acquire a power curve during the operation of the motor and preprocess the power curve to obtain a first target curve, wherein the preprocessing at least includes outlier filtering and missing value completion;

[0078] Specifically, during the operation of the motor, the power data of the motor is collected in real time through the corresponding sensors or monitoring systems. These data are usually in the form of time series, that is, the curve of power changing over time. The power curve data is preprocessed, that is, for the power curve, if there is a sampling point value that is negative or greater than 10 times the average value of all elements in the set, it is identified as abnormal data. For missing data and identified abnormal data values, linear interpolation is used to fill in.

[0079] A calculation unit 20, configured to calculate a correlation coefficient based on the first target curve by a hill climbing algorithm to obtain a target coefficient;

[0080] Specifically, the hill climbing algorithm is a local search algorithm used to find the optimal solution in a given data set. In this step, the hill climbing algorithm is used to analyze the first target curve after preprocessing and calculate one or more correlation coefficients. These coefficients may represent the similarity between different parts of the curve, the continuity of the change trend, or other characteristics related to the state of the disconnector. After processing by the hill climbing algorithm, one or more target coefficients will be obtained, which will serve as the basis for subsequent fault judgment.

[0081] The determination unit 30 is used to compare the target coefficient with the first threshold value to determine whether the isolating switch of the motor fails.

[0082] Specifically, one or more first thresholds are set according to historical data, empirical knowledge or industry standards, and these thresholds are used to define the boundary between the normal working state and the fault state of the isolating switch.

[0083] It can be seen that the embodiment of the present application provides a fault diagnosis device for a motor GIS isolating switch, which includes: an acquisition unit, a calculation unit, and a determination unit. By acquiring and analyzing the power curve during the operation of the motor, the correlation coefficient is calculated using a hill climbing algorithm, and compared with a preset threshold, an effective diagnosis of the motor GIS isolating switch fault is achieved. This method has the advantages of real-time performance and high degree of automation, and helps to improve the efficiency and accuracy of equipment maintenance.

[0084] As a possible implementation manner, the acquisition unit includes: a voltage acquisition module, a current acquisition module and a power curve module.

[0085] The voltage acquisition module is used to monitor the voltage of the motor in real time through a voltage sensor to obtain a second target curve; the current acquisition module is used to monitor the voltage of the motor in real time through a current sensor to obtain a third target curve; the power curve module is used to calculate based on the second target curve and the third target curve to obtain the power curve during the operation of the motor.

[0086] Specifically, the voltage and current of the motor are collected through a voltage sensor and a current sensor, and the real-time voltage value and current value are multiplied to obtain a power curve during the operation of the motor.

[0087] As a possible implementation manner, the acquisition unit further includes: a first traversal module, a first target module and a filtering module.

[0088] A first traversal module is used to traverse the power curve, and when the value of any sampling point is less than the second threshold, determine the sampling point as the first target sampling point;

[0089] Specifically, the system checks each sampling point in the power curve in turn, and each sampling point represents a power value at a certain moment. The second threshold is usually set based on experience or historical data to distinguish between a normal operating state and an abnormal state.

[0090] A first target module, used to determine a sampling point as a first target sampling point when a value of any sampling point is greater than or equal to a mean value of other sampling points in the power curve;

[0091] Specifically, while determining the first target sample point, the mean of all sampling points in the power curve except the first target sample point is calculated. For each sampling point, if its value is greater than or equal to the above-calculated mean, the sampling point is determined as the first target sample point. This step is mainly to screen out those sampling points that are obviously deviated from the normal operating state.

[0092] The filtering module is used to delete the first target sample point in the power curve to complete the outlier filtering of the power curve.

[0093] Specifically, all data points in the power curve marked as the first target sample points are deleted, which helps to eliminate abnormal fluctuations in the power curve and ensure the basic data quality for subsequent analysis.

[0094] In summary, in the preprocessing stage of the motor GIS disconnector fault diagnosis method, the system can effectively preprocess the power curve, remove abnormal values, and retain data reflecting the normal operation of the motor. This not only improves the accuracy of fault diagnosis, but also ensures the reliability and stability of the analysis results. So that subsequent analysis can accurately reflect the operating status of the motor.

[0095] As a possible implementation manner, the acquisition unit further includes: a second traversal module and a completion module.

[0096] The second traversal module is used to traverse the power curve and determine the missing sampling points in the power curve as the second target sampling points; the completion module is used to complete the second target sampling points based on the linear interpolation method to obtain the first target curve.

[0097] Specifically, linear interpolation is a simple and effective interpolation method that assumes that the data change between two known data points is linear. Through the above steps, the system can effectively pre-process the power curve, fill in the missing sampling points, and ensure the integrity of the power curve.

[0098] As a possible implementation manner, the calculation unit includes: a second target module and a substitution module.

[0099] The second target module is used to randomly intercept the first target curve based on the first preset step size to obtain a second target curve P 1 =[p 11 ,p 12 ,…,p 1n ] and P 2 =[p 21 ,p 22 ,…,p 2n ];

[0100] Specifically, a random starting point is selected, and a data segment having a length of a first preset step length is intercepted to form a second target curve. This step ensures that the intercepted data segment can reflect the running state of the motor and has a certain degree of randomness.

[0101] Substitution module, used to substitute the second target curve into the first preset formula Based on the hill climbing algorithm, the second target power curve P 2 =[p 21 ,p 22 ,…,p 2n ] is optimized so that R(P 1 ,P 2 ) to obtain the maximum value and obtain the target coefficient, where E is the mathematical expectation value.

[0102] Through the above steps, the system can calculate the correlation coefficient based on the first target curve through the hill climbing algorithm to obtain the target coefficient. This process not only improves the accuracy of fault diagnosis, but also ensures the reliability and stability of the analysis results.

[0103] As a possible implementation, the substitution module includes: a setting submodule, a construction submodule, a substitution submodule, an update submodule and a target coefficient submodule.

[0104] A submodule is provided for configuring the power curve P according to the second target power curve P 1 =[p 11 ,p 12 ,…,p 1n ] and P 2 =[p 21 ,p 22 ,…,p 2n ], set the objective function N is a natural number;

[0105] A construction submodule is used to take an arbitrary value of the independent variable x as the current solution, and to construct a neighborhood set based on the initial solution and the second preset step size;

[0106] Specifically, the initial solution x=0 can be selected; the neighborhood set N(x)=[xm,x-m+1,…,x+m] is selected, where m is a set neighborhood range parameter, and m=10 is usually taken in the specific implementation of the invention.

[0107] The substitution submodule is used to substitute the samples in the neighborhood set into the objective function, and determine the independent variable x that makes the objective function achieve the maximum value as the optimal solution of the current neighborhood set;

[0108] Specifically, the optimal solution is selected, and the solution that maximizes the objective function is selected from the neighborhood set:

[0109] An updating submodule is used to update the neighborhood set with the optimal solution as the current solution and update the optimal solution based on the updated neighborhood set until the optimal solution is the same in two consecutive updating processes or the number of updates reaches the maximum number, thereby obtaining the target solution;

[0110] The target coefficient submodule is used to substitute the target solution into the first preset formula to obtain the target coefficient.

[0111] Specifically, the neighborhood set N(x') and the optimal solution calculation are repeatedly updated until the optimal solution is found as E(P 1 P 2 ), then the correlation coefficient can be calculated The basis for judging the failure of the isolating switch is as follows: for any power curve P, the qualified standard is minR(P,P i)≥0.95, where Pi is any historical comparison power curve set or phase-to-phase comparison power curve set.

[0112] Through the above steps, the system can optimize the second target power curve based on the hill climbing algorithm so that its correlation with the reference data reaches the maximum value, thereby obtaining the target coefficient. This process not only improves the accuracy of fault diagnosis, but also ensures the reliability and stability of the analysis results.

[0113] As a possible implementation manner, the determining unit includes: a first determining module and a second determining module.

[0114] The first determination module is used to determine that the motor's isolating switch is not faulty when the minimum value of the target coefficient is greater than or equal to the first threshold; the second determination module is used to determine that the motor's isolating switch is faulty when the minimum value of the target coefficient is less than the first threshold.

[0115] Through the above steps, the system can accurately determine whether the isolating switch of the motor is faulty based on the comparison between the target coefficient and the first threshold value.

[0116] The fault diagnosis device for the motor GIS disconnector includes a processor and a memory. The acquisition unit, the calculation unit and the determination unit are stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0117] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the communication efficiency can be improved by adjusting the kernel parameters.

[0118] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0119] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the fault diagnosis method of the motor GIS isolation switch.

[0120] An embodiment of the present invention provides a motor, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a fault diagnosis method for executing the above-mentioned motor GIS disconnect switch.

[0121] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0122] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0123] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0124] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0126] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0127] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0128] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0129] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0130] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0131] 1) The fault diagnosis method of the motor GIS disconnector of the present application first obtains the power curve during the operation of the motor, and pre-processes the power curve to obtain the first target curve, and the pre-processing includes at least outlier filtering and missing value completion; then the correlation coefficient is calculated based on the first target curve by a hill climbing algorithm to obtain the target coefficient; finally, the target coefficient and the first threshold are compared to determine whether the disconnector of the motor fails. The present application draws a power curve based on the current and voltage of the motor, and makes a correlation judgment based on the power curve optimized by the hill climbing algorithm. Compared with the threshold judgment by the average value of characteristic quantities such as motor current, spindle angle and image information in the prior art, the present application makes a judgment by the correlation coefficient, which avoids interference from different periods of the power curve and solves the problem of low accuracy in judging the failure of the mechanism being blocked or not in place in the prior art.

[0132] 2) The fault diagnosis device of the motor GIS disconnector of the present application includes: an acquisition unit, a calculation unit and a determination unit. By acquiring and analyzing the power curve during the operation of the motor, the correlation coefficient is calculated using a hill climbing algorithm and compared with a preset threshold, thereby achieving effective diagnosis of the motor GIS disconnector fault. This method has the advantages of real-time performance and high degree of automation, and helps to improve the efficiency and accuracy of equipment maintenance.

[0133] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A fault diagnosis method for a motor GIS isolating switch, characterized in that: include: Acquire a power curve during the operation of the motor, and preprocess the power curve to obtain a first target curve, wherein the preprocessing includes at least outlier filtering and missing value completion; Based on the first target curve, a correlation coefficient is calculated by a hill climbing algorithm to obtain a target coefficient; A comparison is performed based on the target coefficient and a first threshold value to determine whether a disconnector of the motor fails.

2. The method according to claim 1, characterized in that Get the power curve of the motor during operation, including: The voltage of the motor is monitored in real time by a voltage sensor to obtain a second target curve; The voltage of the motor is monitored in real time by a current sensor to obtain a third target curve; A calculation is performed based on the second target curve and the third target curve to obtain a power curve during operation of the motor.

3. The method according to claim 1, characterized in that Preprocessing the power curve includes: Traversing the power curve, when any sampling point value is less than a second threshold, determining the sampling point as a first target sampling point; When the value of any sampling point is greater than or equal to the average of other sampling points in the power curve, the sampling point is determined as the first target sampling point; The first target sample point in the power curve is deleted to complete outlier filtering of the power curve.

4. The method according to claim 3, characterized in that Preprocessing the power curve to obtain a first target curve also includes: Traversing the power curve, and determining a missing sampling point in the power curve as a second target sampling point; The second target sampling points are complemented based on a linear interpolation method to obtain the first target curve.

5. The method according to claim 1, characterized in that Calculating the correlation coefficient based on the first target curve by using a hill climbing algorithm to obtain a target coefficient includes: The first target curve is randomly intercepted based on a first preset step length to obtain a second target curve P1=[p 11 ,p 12 , … ,p 1n ] and P2 = [p 21 ,p 22 , … ,p 2n ]; Substitute the second target curve into the first preset formula Based on the hill climbing algorithm, the second target power curve P2 = [p 21 ,p 22 ,…,p 2n ] is optimized so that R(P1,P2) reaches the maximum value and obtains the target coefficient, where E is the mathematical expectation value.

6. The method according to claim 5, characterized in that Based on the hill climbing algorithm, the second target power curve P2 = [p 21 ,p 22 ,…,p 2n ] is optimized to maximize R(P1, P2) and obtain the target coefficient, including: According to the second target power curve P1=[p 11 ,p 12 , … ,p 1n ] and P2 = [p 21 ,p 22 , … ,p 2n ], set the objective function N is a natural number; Take any value of the independent variable x as the current solution, and build a neighborhood set based on the initial solution and the second preset step size; Substituting the samples in the neighborhood set into the objective function, determining the independent variable x that makes the objective function obtain the maximum value as the optimal solution of the current neighborhood set; The optimal solution is used as the current solution to update the neighborhood set and the optimal solution is updated based on the updated neighborhood set until the optimal solutions are the same in two consecutive updating processes or the number of updates reaches a maximum number, thereby obtaining a target solution; Substitute the target solution into the first preset formula to obtain the target coefficient.

7. The method according to claim 1, characterized in that Comparing the target coefficient with the first threshold value to determine whether the isolating switch of the motor fails includes: When the minimum value of the target coefficient is greater than or equal to the first threshold, determining that the isolating switch of the motor has not failed; When the minimum value of the target coefficient is smaller than the first threshold, it is determined that the isolation switch of the motor fails.

8. A fault diagnosis device for a motor GIS disconnector, characterized in that: The device comprises: An acquisition unit, used for acquiring a power curve during the operation of the motor, and preprocessing the power curve to obtain a first target curve, wherein the preprocessing includes at least outlier filtering and missing value completion; a calculation unit, configured to calculate a correlation coefficient by a hill climbing algorithm based on the first target curve to obtain a target coefficient; A determination unit is used to compare the target coefficient with a first threshold value to determine whether the isolating switch of the motor fails.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A motor, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 7.

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