Circuit breaker operation life monitoring method, device, equipment and storage medium

Abstract

The present invention relates to the technical field of electrical equipment, and in particular to a circuit breaker operating life monitoring method, device, equipment and storage medium. The present invention obtains the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage; performs feature importance evaluation on the working parameters, the continuous operation time and the historical operation and maintenance information, and determines the target feature parameters according to the evaluation results; constructs a target decision tree model according to the target feature parameters; predicts the remaining operating life of the circuit breaker through the target decision tree model, and performs importance evaluation through the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage, so as to improve the fitting degree of the constructed target decision tree model and improve the accuracy of the predicted service life, thereby avoiding the technical problem that the operating life of the circuit breaker in the prior art is difficult to monitor, resulting in safety hazards in the distribution system.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical equipment, and in particular to a circuit breaker operating life monitoring method, device, equipment and storage medium. Background Art

[0002] Circuit breakers are widely used at the main incoming lines or important equipment of power distribution systems. However, the health status of circuit breakers will show a decline trend during operation. When the decline reaches a certain level, they cannot complete normal work. However, due to the special working mode of circuit breakers, the operating life of the circuit breakers cannot be monitored through normal equipment or status detection. They can only be replaced through regular maintenance, which incurs large costs. In addition, the service life of circuit breakers in different installation locations also varies, resulting in safety hazards in the distribution system.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a circuit breaker service life monitoring method, device, equipment and storage medium, aiming to solve the technical problem in the prior art that the service life of the circuit breaker is difficult to monitor, resulting in safety hazards in the distribution system.

[0005] To achieve the above object, the present invention provides a circuit breaker operation life monitoring method, the method comprising the following steps:

[0006] Obtain the circuit breaker's operating parameters at each stage, continuous operation time, and historical operation and maintenance information;

[0007] Performing feature importance evaluation on the working parameters, the continuous operation time, and the historical operation and maintenance information, and determining target feature parameters according to the evaluation results;

[0008] Constructing a target decision tree model according to the target feature parameters;

[0009] The remaining service life of the circuit breaker is predicted by the target decision tree model.

[0010] Optionally, constructing a target decision tree model according to the target feature parameters includes:

[0011] Determine data subsets corresponding to different values ​​of the target characteristic parameter;

[0012] Constructing leaf nodes of a decision tree model according to the target feature parameters;

[0013] Fill the edges between leaf nodes according to the data subset to obtain multiple candidate decision tree models;

[0014] Each candidate decision tree model is evaluated to obtain the target decision tree model.

[0015] Optionally, evaluating each candidate decision tree model to obtain a target decision tree model includes:

[0016] Input the test sample into each candidate decision tree to obtain the prediction result corresponding to each candidate decision tree;

[0017] Calculate model evaluation parameters according to the test sample and the prediction result;

[0018] A target decision tree model that meets the preset model fitting conditions is selected from each candidate decision tree according to the model evaluation parameters.

[0019] Optionally, the model evaluation parameters include at least: model accuracy, model precision, model recall rate and model false negative rate;

[0020] The calculating of the model evaluation parameter according to the test sample and the prediction result includes:

[0021] Determine and generate a prediction result matrix according to the test sample and the prediction result;

[0022] The prediction structure matrix is:

[0023]

[0024] Correspondingly, the formula for calculating the model accuracy is:

[0025]

[0026] The formula for calculating the model accuracy is:

[0027]

[0028] The formula for calculating the model recall is:

[0029]

[0030] The formula for calculating the false negative rate of the model is:

[0031]

[0032] Among them, x11 is the number of minority samples predicted as minority samples, x10 is the number of minority samples predicted as majority samples, x01 is the number of majority samples predicted as minority samples, and x00 is the number of majority samples predicted as majority samples.

[0033] Optionally, the circuit breaker operation life monitoring method further includes:

[0034] Performing pre-pruning processing on each of the candidate decision trees;

[0035] or

[0036] The target decision tree model is post-pruned.

[0037] Optionally, the performing feature importance evaluation on the working parameter, the continuous operation time, and the historical operation and maintenance information, and determining the target feature parameter according to the evaluation result, includes:

[0038] Generate a candidate data set according to the working parameters, the continuous operation time and the historical operation and maintenance information;

[0039] Calculating the information entropy of the candidate data set;

[0040] Dividing the data set to obtain multiple divided data sets;

[0041] Calculate the information gain and the Gini coefficient between the candidate data set and each divided data set based on the information entropy;

[0042] Performing feature importance evaluation on each divided data set according to the information gain and the Gini coefficient;

[0043] A target partitioning data set and target feature parameters in the target partitioning data set are determined according to the evaluation result.

[0044] Optionally, obtaining the operating parameters of the circuit breaker at each stage includes:

[0045] Obtain the current signal and vibration signal of the circuit in which the circuit breaker is located at each stage;

[0046] Respectively extracting a first time domain feature of the current signal and a second time domain feature and a frequency domain feature of the vibration signal;

[0047] The first time domain feature, the second time domain feature and the frequency domain feature are used as working parameters of a circuit breaker.

[0048] In addition, to achieve the above-mentioned purpose, the present invention further proposes a circuit breaker service life monitoring device, the circuit breaker service life monitoring device comprising:

[0049] The acquisition module is used to obtain the circuit breaker's operating parameters at each stage, continuous operation time, and historical operation and maintenance information;

[0050] An evaluation module, used to evaluate the importance of the working parameters, the continuous operation time and the historical operation and maintenance information, and determine the target characteristic parameters according to the evaluation results;

[0051] A construction module, used to construct a target decision tree model according to the target feature parameters;

[0052] A prediction module is used to predict the remaining service life of the circuit breaker through the target decision tree model.

[0053] In addition, to achieve the above-mentioned purpose, the present invention also proposes a circuit breaker service life monitoring device, which includes: a memory, a processor, and a circuit breaker service life monitoring program stored in the memory and executable on the processor, and the circuit breaker service life monitoring program is configured to implement the steps of the circuit breaker service life monitoring method as described above.

[0054] In addition, to achieve the above objectives, the present invention also proposes a storage medium, on which a circuit breaker service life monitoring program is stored, and when the circuit breaker service life monitoring program is executed by a processor, the steps of the circuit breaker service life monitoring method described above are implemented.

[0055] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the circuit breaker operation life monitoring method as described above are implemented.

[0056] One or more technical solutions proposed in the present invention have at least the following technical effects: the present invention obtains the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage; performs feature importance evaluation on the working parameters, the continuous operation time and the historical operation and maintenance information, and determines the target feature parameters according to the evaluation results; constructs a target decision tree model according to the target feature parameters; predicts the remaining service life of the circuit breaker through the target decision tree model, and performs importance evaluation through the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage, so as to improve the fit of the constructed target decision tree model and the accuracy of the predicted service life, thereby avoiding the technical problem in the prior art that the operating life of the circuit breaker is difficult to monitor, resulting in safety hazards in the distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0058] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0059] Figure 1 It is a flow chart of a first embodiment of a circuit breaker operating life monitoring method of the present invention;

[0060] Figure 2 It is a flow chart of a second embodiment of a circuit breaker operating life monitoring method of the present invention;

[0061] Figure 3 It is a schematic diagram of a decision tree example of an embodiment of a circuit breaker operating life monitoring method of the present invention;

[0062] Figure 4 It is a structural block diagram of the first embodiment of the circuit breaker operation life monitoring device of the present invention;

[0063] Figure 5 It is a structural diagram of a circuit breaker operating life monitoring device in a hardware operating environment involved in an embodiment of the present invention.

[0064] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0065] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0066] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0067] Based on this, an embodiment of the present invention provides a circuit breaker operation life monitoring method, referring to Figure 1 , Figure 1 The figure is a flow chart of a first embodiment of a circuit breaker service life monitoring method according to the present invention.

[0068] In this embodiment, the circuit breaker operation life monitoring method includes:

[0069] Step S10: Obtain the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage.

[0070] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a control computer, etc. The following takes the control computer as an example to illustrate this embodiment and the following embodiments.

[0071] It should be understood that most of the existing circuit breakers are multiplexed circuit breakers, which are equipped with energy storage operating mechanisms. The reliable operation of the energy storage operating mechanism is a prerequisite for the normal opening and closing of the circuit breaker, that is, any problem in any link of the energy storage will affect the opening and closing operation of the circuit breaker, and the mechanical properties of the energy storage operating mechanism of the circuit breaker will be degraded due to wear, jamming, etc. during actual operation. Therefore, when predicting the remaining life of the circuit breaker, this embodiment needs to take the working parameters of the circuit breaker at each stage, the continuous operation time and the historical operation and maintenance information as the basis to establish a model with high accuracy in predicting the operating life.

[0072] Among them, the stage judgment of the circuit breaker is determined by the time interval of the continuous operation time of the circuit breaker, that is, the continuous operation time starts when the circuit breaker is connected to the power distribution system or other load circuits, and the cumulative operation time until the current moment. The historical operation and maintenance information refers to the record of the historical work of the circuit breaker, as well as the record data of short-circuit restart of other circuit breakers of the same model.

[0073] Furthermore, obtaining the working parameters of the circuit breaker at each stage includes:

[0074] Obtain the current signal and vibration signal of the circuit in which the circuit breaker is located at each stage;

[0075] Respectively extracting a first time domain feature of the current signal and a second time domain feature and a frequency domain feature of the vibration signal;

[0076] The first time domain feature, the second time domain feature and the frequency domain feature are used as working parameters of a circuit breaker.

[0077] It should be noted that the first time domain characteristics include at least the mean value, standard deviation, skewness, kurtosis, peak value, and root mean square; the second time domain characteristics include at least the mean value, standard deviation, skewness, kurtosis, peak value, root mean square, amplitude factor, waveform factor, impulse factor, margin factor, energy, and signal duration; the frequency domain characteristics include at least the spectrum kurtosis mean value, spectrum kurtosis standard deviation, spectrum kurtosis kurtosis, and spectrum kurtosis skewness.

[0078] Step S20: performing feature importance evaluation on the working parameters, the continuous operation time and the historical operation and maintenance information, and determining target feature parameters according to the evaluation results.

[0079] In this embodiment, importance assessment refers to determining the parameter that has the greatest impact on the prediction result among the above-mentioned working parameters, continuous operation time, historical operation and maintenance information, that is, the parameter that is judged to be the most important target special diagnosis parameter.

[0080] Furthermore, the performing of feature importance evaluation on the working parameters, the continuous operation time and the historical operation and maintenance information, and determining target feature parameters according to the evaluation results, includes:

[0081] Generate a candidate data set according to the working parameters, the continuous operation time and the historical operation and maintenance information;

[0082] Calculating the information entropy of the candidate data set;

[0083] Dividing the data set to obtain multiple divided data sets;

[0084] Calculate the information gain and the Gini coefficient between the candidate data set and each divided data set based on the information entropy;

[0085] Performing feature importance evaluation on each divided data set according to the information gain and the Gini coefficient;

[0086] A target partitioning data set and target feature parameters in the target partitioning data set are determined according to the evaluation result.

[0087] In the specific implementation, the information entropy of the candidate data set is used to characterize the information lost in the process of the candidate data set from impurity to purity. Purity is related to the influence of each parameter in the candidate data set on the construction of the decision tree model. The more important the parameter is to the decision tree model, the greater the information entropy. Therefore, when the data set is divided, one or more parameters can be separated separately to detect the change in information entropy before and after the data set is divided, thereby realizing the feature importance evaluation of the parameters in the data set.

[0088] Information gain refers to the information entropy before the data set is divided minus the information entropy after the data is divided. Correspondingly, the calculation formula of information entropy is:

[0089]

[0090] Among them, y refers to the number of parameters of each category in the data set, and pk refers to the probability of being classified into category k.

[0091] Correspondingly, the calculation formula of information gain is:

[0092]

[0093] Among them, a is a discrete attribute, and its value is {a1, a2.....av}, and Dv refers to the data set D taking the value a on a. v is a set of samples, |Dv| / |D| is the weight, which indicates the ratio of the number of samples allocated to the parameter to the total number, representing the importance of the parameter.

[0094] The calculation formula of the Gini coefficient is:

[0095]

[0096] Among them, pk refers to the probability of each sample in the data set being classified into category k.

[0097] In this embodiment, the partitioned data set with the largest information gain or the smallest Gini coefficient is used as the data set with the best partitioning effect, and the target feature parameters in the target partitioned data set are extracted.

[0098] Step S30: constructing a target decision tree model according to the target feature parameters.

[0099] The target decision tree model is used to predict the remaining operating life of the circuit breaker based on its current operating parameters and current operating time, thereby avoiding circuit breaker failure and potential safety hazards.

[0100] Step S40: predicting the remaining service life of the circuit breaker by using the target decision tree model.

[0101] This embodiment obtains the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage; performs feature importance evaluation on the working parameters, the continuous operation time and the historical operation and maintenance information, and determines the target feature parameters according to the evaluation results; constructs a target decision tree model according to the target feature parameters; predicts the remaining service life of the circuit breaker through the target decision tree model, and performs importance evaluation through the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage, so as to improve the fit of the constructed target decision tree model and the accuracy of the predicted service life, thereby avoiding the technical problem in the prior art that the operating life of the circuit breaker is difficult to monitor, resulting in safety hazards in the distribution system.

[0102] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S30, comprising:

[0103] Step S301: Determine data subsets corresponding to different values ​​of the target characteristic parameter.

[0104] Step S302: construct leaf nodes of a decision tree model according to the target feature parameters.

[0105] Step S303: Fill the edges between leaf nodes according to the data subset to obtain multiple candidate decision tree models.

[0106] Step S304: Evaluate each candidate decision tree model to obtain a target decision tree model.

[0107] It should be noted that the division criteria of data subsets corresponding to different target characteristic parameters are different. For example, for continuous operation duration, the data collected from January to March, March to June, June to September, and September to December can be classified. For vibration signals, they are divided according to the intervals of parameters such as vibration frequency and vibration amplitude.

[0108] In the specific implementation process, refer to Figure 3 ,Constructing the leaf nodes of the decision tree model and filling the edges between the leaf nodes means taking the important parameters that determine the remaining service life of the circuit breaker as judgment nodes, and then taking the important parameters with different values ​​as branches. For example: if the continuous operation time of the circuit breaker is more than 12 months, it is further judged whether the vibration-current signal meets the initial defined normal range. If not, the remaining service life of the circuit breaker is 0 and needs to be replaced immediately. If it is judged whether the vibration-current signal meets the initial defined normal range, if so, the remaining service life of the circuit breaker is one month, and an early warning is issued to the staff to provide auxiliary maintenance information.

[0109] Since there may be multiple parameters that affect the decision results of the decision tree at the same time, when constructing the decision tree model, multiple candidate decision tree models will be constructed according to different parameter combinations, and each candidate decision tree model will be evaluated to obtain the most accurate decision tree model for predicting the remaining life of the circuit breaker in theory.

[0110] Furthermore, the step of evaluating each candidate decision tree model to obtain a target decision tree model includes:

[0111] Input the test sample into each candidate decision tree to obtain the prediction result corresponding to each candidate decision tree;

[0112] Calculate model evaluation parameters according to the test sample and the prediction result;

[0113] A target decision tree model that meets the preset model fitting conditions is selected from each candidate decision tree according to the model evaluation parameters.

[0114] It should be noted that the test samples include various working parameters, continuous operating time, test data under different operation and maintenance status, and the actual measured service life results. The model evaluation parameters are calculated by statistically analyzing the actual results and the predicted results, so as to optimize or select each candidate decision tree model. The model evaluation parameters include at least: model accuracy, model precision, model recall rate and model false negative rate.

[0115] Further, the calculating model evaluation parameters according to the test sample and the prediction result includes:

[0116] Determine and generate a prediction result matrix according to the test sample and the prediction result;

[0117] The prediction structure matrix is:

[0118]

[0119] Correspondingly, the formula for calculating the model accuracy is:

[0120]

[0121] The formula for calculating the model accuracy is:

[0122]

[0123] The formula for calculating the model recall is:

[0124]

[0125] The formula for calculating the false negative rate of the model is:

[0126]

[0127] Among them, x11 is the number of minority samples predicted as minority samples, x10 is the number of minority samples predicted as majority samples, x01 is the number of majority samples predicted as minority samples, and x00 is the number of majority samples predicted as majority samples.

[0128] Furthermore, model accuracy refers to the proportion of all samples predicted to be correct to the total number of samples. The closer the model accuracy is to 1, the higher the accuracy of the model prediction. Model precision refers to the proportion of actual minority samples among samples predicted to be minority. Recall refers to the proportion of predicted minority samples among samples actually being minority. Model false negative rate is actually 1-model recall.

[0129] The model accuracy, model precision, model recall rate and model false negative rate can be used to determine whether the decision tree model is overfitting. In the case of overfitting, the model fit can be reduced by pruning.

[0130] Furthermore, the circuit breaker operation life monitoring method further includes:

[0131] Performing pre-pruning processing on each of the candidate decision trees;

[0132] or

[0133] The target decision tree model is post-pruned.

[0134] In the specific implementation, pre-pruning is only performed during the process of building a decision tree model, that is, by limiting the maximum depth of the decision tree, the minimum number of samples and other parameters to prevent the decision tree from being too long or too deep; post-pruning means that after the decision tree is built, by evaluating the importance of each sub-branch in the target decision tree, it is determined whether to delete some branches and reduce the model fit.

[0135] This embodiment determines the data subsets corresponding to different values ​​of the target feature parameters; constructs leaf nodes of a decision tree model according to the target feature parameters; fills the edges between the leaf nodes according to the data subsets to obtain multiple candidate decision tree models; evaluates each candidate decision tree model to obtain a target decision tree model, thereby improving the accuracy of the target decision tree model in predicting the operating life of the circuit breaker.

[0136] This application also provides a circuit breaker operation life monitoring device, please refer to Figure 4 , the circuit breaker operation life monitoring device comprises:

[0137] The acquisition module 10 is used to obtain the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage.

[0138] The evaluation module 20 is used to evaluate the importance of the operating parameters, the continuous operation time and the historical operation and maintenance information, and determine the target characteristic parameters according to the evaluation results.

[0139] The construction module 30 is used to construct a target decision tree model according to the target feature parameters.

[0140] The prediction module 40 is used to predict the remaining service life of the circuit breaker through the target decision tree model.

[0141] This embodiment obtains the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage; performs feature importance evaluation on the working parameters, the continuous operation time and the historical operation and maintenance information, and determines the target feature parameters according to the evaluation results; constructs a target decision tree model according to the target feature parameters; predicts the remaining service life of the circuit breaker through the target decision tree model, and performs importance evaluation through the working parameters, continuous operation time and historical operation and maintenance information of the circuit breaker at each stage, so as to improve the fit of the constructed target decision tree model and the accuracy of the predicted service life, thereby avoiding the technical problem in the prior art that the operating life of the circuit breaker is difficult to monitor, resulting in safety hazards in the distribution system.

[0142] In one embodiment, the construction module 30 is also used to determine the data subsets corresponding to different values ​​of the target feature parameters; construct leaf nodes of the decision tree model according to the target feature parameters; fill the edges between the leaf nodes according to the data subset to obtain multiple candidate decision tree models; evaluate each candidate decision tree model to obtain a target decision tree model.

[0143] In one embodiment, the construction module 30 is also used to input the test sample into each candidate decision tree to obtain the prediction result corresponding to each candidate decision tree; calculate the model evaluation parameter according to the test sample and the prediction result; and select the target decision tree model that meets the preset model fitting conditions from each candidate decision tree according to the model evaluation parameter.

[0144] In one embodiment, the construction module 30 is further used for calculating the model evaluation parameters according to the test sample and the prediction result, including: determining and generating a prediction result matrix according to the test sample and the prediction result;

[0145] The prediction structure matrix is:

[0146]

[0147] Correspondingly, the formula for calculating the model accuracy is:

[0148]

[0149] The formula for calculating the model accuracy is:

[0150]

[0151] The formula for calculating the model accuracy is:

[0152]

[0153] The formula for calculating the model accuracy is:

[0154]

[0155] Among them, x11 is the number of minority samples predicted as minority samples, x10 is the number of minority samples predicted as majority samples, x01 is the number of majority samples predicted as minority samples, and x00 is the number of majority samples predicted as majority samples.

[0156] In one embodiment, the construction module 30 is further used to perform pre-pruning processing on each candidate decision tree; or to perform post-pruning processing on the target decision tree model.

[0157] In one embodiment, the evaluation module 20 is also used to generate a candidate data set based on the working parameters, the continuous operation time and the historical operation and maintenance information; calculate the information entropy of the candidate data set; divide the data set to obtain multiple divided data sets; calculate the information gain and Gini coefficient between the candidate data set and each divided data set based on the information entropy; evaluate the feature importance of each divided data set according to the information gain and the Gini coefficient; and determine the target divided data set and the target feature parameters in the target divided data set according to the evaluation results.

[0158] In one embodiment, the acquisition module 10 is also used to obtain the current signal and vibration signal of the circuit in which the circuit breaker is located in each stage; respectively extract the first time domain characteristics of the current signal and the second time domain characteristics and frequency domain characteristics of the vibration signal; and use the first time domain characteristics, the second time domain characteristics and the frequency domain characteristics as the working parameters of the circuit breaker.

[0159] The present application provides a circuit breaker service life monitoring device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the circuit breaker service life monitoring method in the above-mentioned embodiment 1.

[0160] Reference below Figure 5 , which shows a schematic diagram of the structure of a circuit breaker operation life monitoring device suitable for implementing the embodiment of the present application. The circuit breaker operation life monitoring device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The circuit breaker service life monitoring device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0161] like Figure 5As shown, the circuit breaker operation life monitoring device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. Various programs and data required for the operation of the circuit breaker operation life monitoring device are also stored in the RAM 1004. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 may allow the circuit breaker operating life monitoring device to communicate wirelessly or wired with other devices to exchange data. Although the circuit breaker operating life monitoring device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0162] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0163] The circuit breaker operation life monitoring device provided by the present application adopts the circuit breaker operation life monitoring method in the above embodiment, which can solve the technical problem of circuit breaker operation life monitoring. Compared with the prior art, the beneficial effects of the circuit breaker operation life monitoring device provided by the present application are the same as the beneficial effects of the circuit breaker operation life monitoring method provided by the above embodiment, and other technical features in the circuit breaker operation life monitoring device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0164] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0165] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0166] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the circuit breaker operation life monitoring method in the above-mentioned embodiment.

[0167] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0168] The computer-readable storage medium may be included in the circuit breaker service life monitoring device; or may exist independently without being assembled into the circuit breaker service life monitoring device.

[0169] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the circuit breaker service life monitoring device, the circuit breaker service life monitoring device performs circuit breaker service life monitoring.

[0170] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0171] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0172] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0173] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned circuit breaker operation life monitoring method, and can solve the technical problem of circuit breaker operation life monitoring. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the circuit breaker operation life monitoring method provided in the above-mentioned embodiment, and will not be repeated here.

[0174] The present application also provides a computer program product, including a computer program, which implements the steps of the circuit breaker operation life monitoring method as described above when the computer program is executed by a processor.

[0175] The computer program product provided in this application can solve the technical problem of circuit breaker operation life monitoring. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the circuit breaker operation life monitoring method provided in the above embodiment, which will not be repeated here.

[0176] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A circuit breaker service life monitoring method, characterized in that: The circuit breaker operation life monitoring method comprises: Obtain the circuit breaker's operating parameters at each stage, continuous operation time, and historical operation and maintenance information; Performing feature importance evaluation on the working parameters, the continuous operation time, and the historical operation and maintenance information, and determining target feature parameters according to the evaluation results; Constructing a target decision tree model according to the target feature parameters; The remaining service life of the circuit breaker is predicted by the target decision tree model.

2. The method according to claim 1, characterized in that The step of constructing a target decision tree model according to the target feature parameters comprises: Determine data subsets corresponding to different values ​​of the target characteristic parameter; Constructing leaf nodes of a decision tree model according to the target feature parameters; Fill the edges between leaf nodes according to the data subset to obtain multiple candidate decision tree models; Each candidate decision tree model is evaluated to obtain the target decision tree model.

3. The method according to claim 2, characterized in that The step of evaluating each candidate decision tree model to obtain a target decision tree model includes: Input the test sample into each candidate decision tree to obtain the prediction result corresponding to each candidate decision tree; Calculate model evaluation parameters according to the test sample and the prediction result; A target decision tree model that meets the preset model fitting conditions is selected from each candidate decision tree according to the model evaluation parameters.

4. The method according to claim 3, characterized in that The model evaluation parameters include at least: model accuracy, model precision, model recall rate and model false negative rate; The calculating of the model evaluation parameter according to the test sample and the prediction result includes: Determine and generate a prediction result matrix according to the test sample and the prediction result; The prediction structure matrix is: Correspondingly, the formula for calculating the model accuracy is: The formula for calculating the model accuracy is: The formula for calculating the model recall is: The formula for calculating the false negative rate of the model is: Among them, x11 is the number of minority samples predicted as minority samples, x10 is the number of minority samples predicted as majority samples, x01 is the number of majority samples predicted as minority samples, and x00 is the number of majority samples predicted as majority samples.

5. The method according to claim 2, characterized in that The circuit breaker operation life monitoring method further includes: Performing pre-pruning processing on each of the candidate decision trees; or The target decision tree model is post-pruned.

6. The method according to claim 1, characterized in that The performing characteristic importance evaluation on the working parameter, the continuous operation time and the historical operation and maintenance information, and determining the target characteristic parameter according to the evaluation result, includes: Generate a candidate data set according to the working parameters, the continuous operation time and the historical operation and maintenance information; Calculating the information entropy of the candidate data set; Dividing the data set to obtain multiple divided data sets; Calculate the information gain and the Gini coefficient between the candidate data set and each divided data set based on the information entropy; Performing feature importance evaluation on each divided data set according to the information gain and the Gini coefficient; A target partitioning data set and target feature parameters in the target partitioning data set are determined according to the evaluation result.

7. The method according to claim 1, characterized in that The obtaining of the working parameters of the circuit breaker at each stage includes: Obtain the current signal and vibration signal of the circuit in which the circuit breaker is located at each stage; Respectively extracting a first time domain feature of the current signal and a second time domain feature and a frequency domain feature of the vibration signal; The first time domain feature, the second time domain feature and the frequency domain feature are used as working parameters of a circuit breaker.

8. A circuit breaker service life monitoring device, characterized in that: The circuit breaker operation life monitoring device comprises: The acquisition module is used to obtain the circuit breaker's operating parameters at each stage, continuous operation time, and historical operation and maintenance information; An evaluation module, used to evaluate the importance of the working parameters, the continuous operation time and the historical operation and maintenance information, and determine the target characteristic parameters according to the evaluation results; A construction module, used to construct a target decision tree model according to the target feature parameters; A prediction module is used to predict the remaining service life of the circuit breaker through the target decision tree model.

9. A circuit breaker service life monitoring device, characterized in that: The circuit breaker service life monitoring device comprises: a memory, a processor, and a circuit breaker service life monitoring program stored in the memory and executable on the processor, wherein the circuit breaker service life monitoring program is configured to implement the steps of the circuit breaker service life monitoring method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a circuit breaker service life monitoring program, and when the circuit breaker service life monitoring program is executed by the processor, the steps of the circuit breaker service life monitoring method according to any one of claims 1 to 7 are implemented.

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