Method, system and storage medium for detecting partial discharge phenomena of switchgear equipment

Abstract

The application provides a detection method and system for partial discharge of a switch cabinet device and a storage medium. The method comprises: simultaneously collecting pulse current signal data of a plurality of switch cabinet devices to obtain initial pulse current signals corresponding to the switch cabinet devices; preprocessing the initial pulse current signals of the switch cabinet devices to obtain target pulse current signals corresponding to the switch cabinet devices; establishing a partial discharge early warning model, which is used to determine whether the switch cabinet device has a partial discharge phenomenon; and determining the current partial discharge state of each switch cabinet device according to the target pulse current signal and the partial discharge early warning model, wherein the current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet device at the current time. The method establishes the partial discharge early warning model, judges the uploaded real-time partial discharge data, outputs the corresponding judgment result, realizes remote inspection of the partial discharge of the switch cabinet device by the operation and maintenance personnel, effectively reduces the labor cost, and improves the monitoring efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of switch cabinet detection, in particular, to a detection method for partial discharge phenomenon of switch cabinet equipment, a detection system for partial discharge phenomenon of switch cabinet equipment, a computer readable storage medium and an electronic device. BACKGROUND

[0002] With the gradual increase of power equipment capacity, the scale of power distribution equipment is also increasing, while the number of operation and maintenance personnel is declining. Traditional manual periodic inspection and maintenance cannot meet the current rapid growth of power demand.

[0003] In 10kV distribution network equipment, the number of switch cabinets is large. It is very time-consuming, labor-intensive and costly to detect whether there is a discharge problem in electrical equipment by using traditional manual detection methods.

[0004] The traditional partial discharge detection method for switch cabinet equipment in power distribution room often has one data acquisition device corresponding to one switch cabinet equipment, which cannot realize "one-to-many" simultaneous acquisition. It needs to manually collect data from different switch cabinet equipment multiple times, which is easy to miss inspection and cause equipment problems. At the same time, due to excessive reliance on manpower, it causes waste of human resources, high detection cost and low detection efficiency. SUMMARY

[0005] The main purpose of the present application is to provide a detection method for partial discharge phenomenon of switch cabinet equipment, a detection system for partial discharge phenomenon of switch cabinet equipment, a computer readable storage medium and an electronic device, so as to at least solve the problem that the traditional partial discharge detection method for switch cabinet equipment can only detect one switch cabinet equipment at a time, cannot realize "one-to-many" simultaneous acquisition, and has large consumption of human resources, high detection cost and low efficiency.

[0006] In order to achieve the above purpose, according to one aspect of the present application, a detection method for partial discharge phenomenon of switch cabinet equipment is provided, which comprises: simultaneously collecting pulse current signal data of multiple switch cabinet equipment to obtain initial pulse current signal corresponding to each switch cabinet equipment; preprocessing the initial pulse current signal of each switch cabinet equipment to obtain target pulse current signal corresponding to each switch cabinet equipment; establishing a partial discharge early warning model, the partial discharge early warning model being used to determine whether the switch cabinet equipment has a partial discharge phenomenon; determining the current partial discharge state of each switch cabinet equipment according to the target pulse current signal and the partial discharge early warning model, the current partial discharge state representing the existence state of the partial discharge phenomenon of the switch cabinet equipment at the current time.

[0007] Optionally, the pulse current signal data of all the switch cabinet devices are collected simultaneously by using the same collection device, the collection device comprises a plurality of data collection interfaces, the data collection interfaces correspond to the switch cabinet devices one by one, the collection device comprises an alarm function, and the alarm function of the collection device is used to send alarm information when the switch cabinet device has partial discharge phenomenon.

[0008] Optionally, the initial pulse current signal of each switch cabinet device is preprocessed to obtain the target pulse current signal corresponding to each switch cabinet device, including: determining whether there is missing data in the initial pulse current signal of each switch cabinet device; in the case that there is no missing data in the initial pulse current signal, the initial pulse current signal is determined as the target pulse current signal corresponding to the switch cabinet device; and in the case that there is missing data in the initial pulse current signal, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet device.

[0009] Optionally, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet device, including: constructing a forward neural network model, wherein the neural network model is trained using a plurality of sets of training data, each set of training data in the plurality of sets of training data includes historical pulse current signals of the switch cabinet device and historical related operating data of the switch cabinet device corresponding to the historical pulse current signals obtained in a historical time period, and the historical related operating data includes voltage values and device temperatures of the switch cabinet device in the historical time period; and the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet device.

[0010] Optionally, the missing data is predicted and supplemented using the neural network model to obtain the target pulse current signal corresponding to the switch cabinet device, including: obtaining a data supplement formula K = f(t, v, w), wherein K represents the predicted missing value, t represents a specific time period of a prediction day, v represents a voltage value of the switch cabinet device on the prediction day, w represents a temperature of the switch cabinet device on the prediction day, and f() represents a neural network model; and the missing data is predicted and supplemented according to the data supplement formula to obtain the target pulse current signal corresponding to the switch cabinet device.

[0011] Optionally, the current partial discharge state of each of the switch cabinet equipment is determined according to the target pulse current signal and the partial discharge early warning model, including: analyzing and calculating the target pulse current signal based on the principle of pulse current method to obtain the corresponding apparent discharge quantity of the switch cabinet equipment; inputting the apparent discharge quantity into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, and the current partial discharge state includes no partial discharge phenomenon, partial discharge phenomenon, and hidden danger of partial discharge phenomenon.

[0012] Optionally, the current partial discharge state of each of the switch cabinet equipment is determined according to the target pulse current signal and the partial discharge early warning model, including: analyzing and calculating the target pulse current signal based on the principle of pulse current method to obtain the corresponding apparent discharge quantity of the switch cabinet equipment; inputting the apparent discharge quantity into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, and the current partial discharge state includes no partial discharge phenomenon, partial discharge phenomenon, and hidden danger of partial discharge phenomenon.

[0013] According to another aspect of the present application, a detection system for partial discharge phenomenon of switch cabinet equipment is provided, including: a detection device for partial discharge phenomenon of switch cabinet equipment, configured to execute any one of the detection methods for partial discharge phenomenon of switch cabinet equipment; and a collection device, which is connected to the detection device for partial discharge phenomenon of switch cabinet equipment through wireless Bluetooth communication.

[0014] According to another aspect of the present application, a computer readable storage medium is provided, which includes a stored program, wherein the program controls the device where the computer readable storage medium is located to execute any one of the detection methods for partial discharge phenomenon of switch cabinet equipment when the program is running.

[0015] According to another aspect of the present application, an electronic device is provided, including: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include a detection method for partial discharge phenomenon of switch cabinet equipment.

[0016] With the technical solution of the present application, the detection method of the partial discharge phenomenon of the switch cabinet equipment first simultaneously collects pulse current signal data of multiple switch cabinet equipments to obtain initial pulse current signals corresponding to each switch cabinet equipment; the initial pulse current signals of each switch cabinet equipment are preprocessed to obtain target pulse current signals corresponding to each switch cabinet equipment; a partial discharge early warning model is established, which is used to determine whether the switch cabinet equipment has a partial discharge phenomenon; according to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each switch cabinet equipment is determined, and the current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet equipment at the current time. The method simultaneously collects the pulse current signal data of multiple switch cabinets in the power distribution room in real time by using the improved centralized data collection equipment, and uploads the data to the data center; the data center preprocesses the collected pulse current signal data and converts it into partial discharge data, at the same time, based on the actual work experience of the operation and maintenance site, a partial discharge early warning model is constructed to judge the uploaded real-time partial discharge data and output the corresponding judgment result. The method realizes remote inspection of the partial discharge of the switch cabinet equipment by the operation and maintenance personnel, effectively reduces the labor cost, improves the monitoring efficiency, solves the problem that the traditional switch cabinet equipment partial discharge detection method can only detect one switch cabinet equipment at a time, cannot realize "one-to-many" simultaneous collection, and the labor resource consumption is large, the detection cost is high and the efficiency is low. BRIEF DESCRIPTION OF DRAWINGS

[0017] The drawings accompanying the specification of the present application form a part thereof, serve to provide further understanding of the present application, and together with the description of the present application, serve to explain the present application, and do not constitute improper limitations to the present application. In the drawings:

[0018] Figure 1 A hardware structure block diagram of a mobile terminal for executing a detection method of a partial discharge phenomenon of a switch cabinet equipment according to an embodiment of the present application is shown;

[0019] Figure 2 A flowchart of a detection method of a partial discharge phenomenon of a switch cabinet equipment according to an embodiment of the present application is shown;

[0020] Figure 3 A comparison diagram of a detection method of a partial discharge phenomenon of a switch cabinet equipment according to an embodiment of the present application and prior art is shown;

[0021] Figure 4 A flowchart of another detection method of a partial discharge phenomenon of a switch cabinet equipment according to an embodiment of the present application is shown;

[0022] Figure 5 A structure block diagram of a detection system of a partial discharge phenomenon of a switch cabinet equipment according to an embodiment of the present application is shown;

[0023] Figure 6 A structural block diagram of a detection device for partial discharge phenomenon of a switch cabinet device is shown according to an embodiment of the present application.

[0024] Among them, the above-mentioned drawings include the following reference signs:

[0025] 001, a detection device for partial discharge phenomenon of a switch cabinet device; 002, an acquisition device; 102, a processor; 104, a memory; 106, a transmission device; 108, an input and output device. DETAILED DESCRIPTION

[0026] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The technical solutions in the embodiments of the present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0027] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, not necessarily to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] As introduced in the background, the traditional partial discharge detection method of switch cabinet equipment in power distribution room often has one data acquisition device corresponding to one switch cabinet equipment, which cannot realize "one-to-many" simultaneous acquisition, and needs manual multiple data acquisition monitoring of different switch cabinet equipment, which is easy to miss inspection and equipment problems. At the same time, due to excessive dependence on manpower, it causes waste of resources, high monitoring cost and low monitoring efficiency.

[0030] To address the problems of traditional partial discharge detection methods for switchgear equipment, which can only detect one switchgear device at a time, cannot achieve simultaneous "one-to-many" data acquisition, and are characterized by high manpower consumption, high detection costs, and low efficiency, embodiments of this application provide a method for detecting partial discharge phenomena in switchgear equipment, a detection system for partial discharge phenomena in switchgear equipment, a computer-readable storage medium, and an electronic device.

[0031] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0032] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a method of detecting partial discharge phenomena in switchgear equipment according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0033] The memory 104 can be used to store computer programs, such as software programs of application software and modules, such as the computer program corresponding to the detection method of partial discharge phenomenon of switch cabinet equipment in the embodiments of the present application. The processor 102 can execute various functional applications and data processing, i.e., implement the above method, by running the computer program stored in the memory 104. The memory 104 can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include a memory remotely arranged with respect to the processor 102, and the remote memory can be connected to the mobile terminal through a network. Examples of the 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 specific examples of the network can include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (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 can be a radio frequency (RF) module, which is used to communicate with the Internet in a wireless manner.

[0034] In the embodiments, a detection method of partial discharge phenomenon of switch cabinet equipment 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 the 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.

[0035] Figure 2 is a flowchart of the detection method of partial discharge phenomenon of switch cabinet equipment according to the embodiments of the present application. As shown in Figure 2 , the method includes the following steps:

[0036] In step S201, pulse current signal data of a plurality of switch cabinet equipment is collected simultaneously to obtain initial pulse current signals corresponding to each of the switch cabinet equipment.

[0037] Specifically, first, the pulse current data of the switch cabinet equipment in the power distribution room is collected by using a data collection device. The pulse current data of the switch cabinet in the power distribution room is collected simultaneously by using the improved centralized data collection device, and the real-time data is transmitted to the data center through the wireless Bluetooth communication mode.

[0038] Wherein, all the above switch cabinet equipment pulse current signal data is obtained by using the same collection device, the collection device includes a plurality of data collection interfaces, the data collection interface corresponds to the switch cabinet equipment, the collection device includes an alarm function, the alarm function of the collection device is used to send alarm information when the switch cabinet equipment occurs partial discharge phenomenon.

[0039] Specifically, this can simultaneously collect the pulse current signal data of multiple switch cabinets in the power distribution room in real time, realize remote inspection of switch cabinet partial discharge by operation and maintenance personnel, effectively reduce labor cost, and improve monitoring efficiency. Among them, the collection device collects full switch cabinet equipment operation data every 15 minutes and uploads to the data center.

[0040] The traditional collection device has only one data interface. If there are multiple switch cabinets in an electrical room, the data collection of all switch cabinets can be completed by unplugging and plugging multiple times. The multi-data interface of the collection device can be plugged into multiple switch cabinets at the same time to collect data, and the data collection can be completed by unplugging and plugging once. The data collection interface of the traditional partial pulse current data collection device of the switch cabinet equipment in the power distribution room is transformed, and the external data collection interface is expanded, which can be customized according to the actual needs of the scene. Active alarm uploading is set, and once the pulse current data collected by a switch cabinet reaches the preset alarm value, it will be actively uploaded.

[0041] Step S202, preprocessing the initial pulse current signal of each switch cabinet equipment to obtain the target pulse current signal corresponding to each switch cabinet equipment;

[0042] Specifically, the uploaded pulse current signal data is preprocessed. First, it is judged whether there is a missing value. If there is no missing value, the uploaded pulse current data is directly analyzed and calculated based on the principle of pulse current method to obtain the corresponding apparent discharge quantity. The "apparent discharge quantity" refers to the same change in the voltage of the test product at both ends of the power equipment partial discharge and the change in the voltage at both ends of the partial discharge. At this time, the charge quantity injected is called the apparent discharge quantity of the partial discharge. It should be noted that the apparent discharge quantity in the present embodiment is directly obtained by the instrument, and no detailed description is given.

[0043] Wherein, the initial pulse current signal of each switch cabinet equipment is preprocessed to obtain the target pulse current signal corresponding to each switch cabinet equipment, including the following steps:

[0044] Step S301, determining whether there is missing data in the initial pulse current signal of each switch cabinet equipment;

[0045] Step S302, in the case where the initial pulse current signal does not contain the missing data, the initial pulse current signal is determined as the target pulse current signal corresponding to the switch cabinet equipment.

[0046] Step S303, in the case where the initial pulse current signal contains the missing data, the missing data is supplemented by prediction to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0047] Specifically, this can accurately supplement the missing values and ensure the integrity of the data to ensure the accuracy of the subsequent switch cabinet partial discharge phenomenon judgment.

[0048] The missing data is supplemented by prediction to obtain the target pulse current signal corresponding to the switch cabinet equipment, including the following steps:

[0049] Step S401, a forward neural network model is constructed, wherein the neural network model is trained using a plurality of sets of training data, each set of training data in the plurality of sets of training data includes historical pulse current signals of the switch cabinet equipment and historical related operating data of the switch cabinet equipment corresponding to the historical pulse current signals obtained in a historical time period, and the historical related operating data includes voltage values and equipment temperatures of the switch cabinet equipment in the historical time period.

[0050] Step S402, the missing data is supplemented by prediction using the neural network model to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0051] Specifically, the missing data is supplemented by prediction using the neural network, which can make the supplemented missing data closer to the real data and increase the accuracy of the data. That is, if there is data missing, the neural network model is introduced to supplement the missing data, and then the obtained pulse current data is analyzed and calculated based on the principle of the pulse current method to obtain the corresponding apparent discharge quantity.

[0052] The training data is historical data in the same period of the previous three months on the prediction day, which is used as a training data set to train the forward neural network model, and then the relevant operating data on the day is input to output the prediction result at this time.

[0053] The missing data is supplemented by prediction using the neural network model to obtain the target pulse current signal corresponding to the switch cabinet equipment, including the following steps:

[0054] In step S4021, a data supplement formula K=f(t, v, w) is obtained, where K represents a predicted missing value, t represents a specific time period of a prediction day, v represents a voltage value of the switch cabinet equipment on the prediction day, w represents a temperature of the switch cabinet equipment on the prediction day, and f() represents a neural network model.

[0055] In step S4022, the missing data is predicted and supplemented according to the data supplement formula, to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0056] Specifically, the missing data is predicted and supplemented by the neural network, so that the accuracy of the data is increased.

[0057] The structure of the forward neural network model is shown in Table 1.

[0058] Table 1, structure table of the forward neural network model

[0059] Input layer features 1 -dimensional Number of hidden layer neurons 100 Output layer features 1 -dimensional Initial learning rate 0.01 Number of training steps 1000 steps

[0060] In step S203, a partial discharge early warning model is established, which is used to determine whether the switch cabinet equipment has a partial discharge phenomenon.

[0061] Specifically, the partial discharge early warning model is established to analyze and judge the data, and output a judgment result. In the process of monitoring the partial discharge, the monitoring result is often disturbed by some high-frequency signals from the outside, causing false alarm phenomenon.

[0062] In step S204, the current partial discharge state of each switch cabinet equipment is determined according to the target pulse current signal and the partial discharge early warning model, and the current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet equipment at the current time.

[0063] Specifically, by setting different alarm logics, the false alarm rate is reduced, and the alarm accuracy is improved.

[0064] The current partial discharge state of each switch cabinet equipment is determined according to the target pulse current signal and the partial discharge early warning model, including the following steps:

[0065] In step S501, the target pulse current signal is analyzed and calculated based on the principle of the pulse current method, to obtain the apparent discharge quantity corresponding to the switch cabinet equipment.

[0066] In step S502, the apparent discharge quantity is input into the partial discharge early warning model, to obtain the current partial discharge state of the switch cabinet equipment, and the current partial discharge state includes no partial discharge phenomenon, partial discharge phenomenon, and partial discharge phenomenon hidden danger.

[0067] Specifically, this can avoid some high-frequency signal interference from the outside world, causing false alarm phenomenon.

[0068] The current partial discharge state of the switch cabinet equipment is obtained by inputting the apparent discharge quantity into the partial discharge early warning model, and includes the following steps:

[0069] In step S5021, if the apparent discharge quantity is less than the first preset value, the current partial discharge state of the switch cabinet equipment is determined as no partial discharge phenomenon, and the current partial discharge value of the switch cabinet equipment is output.

[0070] In the above method, the full-quantity switch cabinet equipment operation data is collected once every 15 minutes and uploaded to the data center. If the eight sampling points collected continuously for 2 hours for the same switch cabinet equipment are all less than the first preset value, the current partial discharge state of the switch cabinet equipment is determined as no partial discharge phenomenon. The first preset value is 450.

[0071] In step S5022, if the apparent discharge quantity is greater than or equal to the first preset value and less than the second preset value, the current partial discharge state of the switch cabinet equipment is determined as having partial discharge phenomenon hidden danger, and an early warning information is issued.

[0072] In the above method, the full-quantity switch cabinet equipment operation data is collected once every 15 minutes and uploaded to the data center. If the eight sampling points collected continuously for 2 hours for the same switch cabinet equipment are all greater than or equal to the first preset value and less than the second preset value, the current partial discharge state of the switch cabinet equipment is determined as having partial discharge phenomenon hidden danger. The second preset value is 900.

[0073] In step S5023, if the apparent discharge quantity is greater than or equal to the second preset value, the current partial discharge state of the switch cabinet equipment is determined as having partial discharge phenomenon, and an alarm information is issued.

[0074] In the above method, the full-quantity switch cabinet equipment operation data is collected once every 15 minutes and uploaded to the data center. If the eight sampling points collected continuously for 2 hours for the same switch cabinet equipment are all greater than or equal to the second preset value, the current partial discharge state of the switch cabinet equipment is determined as having partial discharge phenomenon.

[0075] Specifically, by setting different alarm logic, the false alarm rate is reduced, and the alarm accuracy is improved.

[0076] The above-mentioned detection method of the partial discharge phenomenon of the switch cabinet device of the present application firstly simultaneously collects pulse current signal data of multiple switch cabinet devices to obtain initial pulse current signals corresponding to each switch cabinet device; the initial pulse current signals of each switch cabinet device are preprocessed to obtain target pulse current signals corresponding to each switch cabinet device; a partial discharge early warning model is established, which is used to determine whether the switch cabinet device has a partial discharge phenomenon; and the current partial discharge state of each switch cabinet device is determined according to the target pulse current signal and the partial discharge early warning model, and the current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet device at the current time. The method simultaneously collects the pulse current signal data of multiple switch cabinet devices of the distribution room in real time by using the improved centralized data collection device, and uploads the data to the data center; the data center preprocesses the collected pulse current signal data and converts it into partial discharge data, at the same time, based on the actual work experience of the operation and maintenance site, a partial discharge early warning model is constructed to judge the uploaded real-time partial discharge data and output the corresponding judgment result. The method realizes remote inspection of the partial discharge of the switch cabinet device by the operation and maintenance personnel, effectively reduces the labor cost, improves the monitoring efficiency, solves the problem that the traditional switch cabinet device partial discharge detection method can only detect one switch cabinet device at a time, cannot realize "one-to-many" simultaneous collection, and consumes a lot of human resources and has high detection cost and low efficiency.

[0077] Figure 3 For a comparison chart of the detection method of the partial discharge phenomenon of a switch cabinet device and the prior art, as shown in Figure 3 The traditional switch cabinet device partial pulse current data collection device of the distribution room only has a single data collection interface and no alarm active uploading function, while the improved centralized switch cabinet device partial pulse current data collection device of the distribution room of the present application has multiple data collection interfaces, which can be customized according to the number of switch cabinet devices of the distribution room, and is provided with an alarm active uploading function.

[0078] In order for those skilled in the art to more clearly understand the technical solutions of the present application, the implementation process of the detection method of the partial discharge phenomenon of the switch cabinet device of the present application will be described in detail below in combination with specific embodiments.

[0079] The present embodiment relates to a specific detection method of the partial discharge phenomenon of a switch cabinet device, as shown in Figure 4 The present embodiment relates to a specific detection method of the partial discharge phenomenon of a switch cabinet device, as shown in

[0080] Step S1: collecting pulse current data of switch cabinet devices of a distribution room by a collection device;

[0081] Step S2: preprocessing the uploaded pulse current signal data;

[0082] Step S3: Establish a partial discharge early warning model, analyze and judge the data, generate alarm information and notify the operation and maintenance personnel to verify the alarm if the alarm logic is met;

[0083] Step S4: Output the current partial discharge value if the alarm logic is not met.

[0084] This application also provides a detection system for partial discharge phenomena in switchgear equipment, such as... Figure 5 As shown, it includes: a detection device 001 for detecting partial discharge phenomena in switchgear equipment, used to perform any of the above-described detection methods for partial discharge phenomena in switchgear equipment; and a data acquisition device 002, which is wirelessly connected to the detection device 001 for partial discharge phenomena in switchgear equipment via Bluetooth communication.

[0085] The partial discharge detection system for switchgear equipment described in this application utilizes a modified centralized data acquisition device to simultaneously collect pulse current data from all switchgear in the power distribution room. Real-time data is transmitted to a data center via wireless Bluetooth communication. The system not only modifies the data acquisition interface of traditional switchgear partial pulse current data acquisition equipment by expanding it with an external data acquisition interface that can be customized to meet specific site requirements, but also includes an active alarm transmission feature. Once the pulse current data collected from a switchgear reaches a preset alarm value, the system immediately transmits the alarm. This method enables remote inspection of partial discharge in switchgear equipment by maintenance personnel, effectively reducing labor costs, improving monitoring efficiency, and solving the problems of traditional partial discharge detection methods that can only detect one switchgear at a time, cannot achieve simultaneous "one-to-many" data acquisition, and suffer from high manpower consumption, high detection costs, and low efficiency.

[0086] This application also provides a detection device for partial discharge phenomena in switchgear equipment. It should be noted that the detection device for partial discharge phenomena in switchgear equipment in this application can be used to execute the detection method for partial discharge phenomena in switchgear equipment provided in this application. This device is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0087] The following describes the detection device for partial discharge phenomena in switchgear equipment provided in the embodiments of this application.

[0088] Figure 6 This is a schematic diagram of a detection device for partial discharge phenomena in switchgear equipment according to an embodiment of this application. Figure 6As shown, the device comprises a collection unit 10, a first processing unit 20, a second processing unit 30 and a determination unit 40, the collection unit 10 is used to simultaneously collect pulse current signal data of a plurality of switch cabinet devices, to obtain initial pulse current signal corresponding to each of the above switch cabinet devices; the first processing unit 20 is used to pre-process the initial pulse current signal of each of the above switch cabinet devices, to obtain a target pulse current signal corresponding to each of the above switch cabinet devices; the second processing unit 30 is used to establish a partial discharge early warning model, the partial discharge early warning model is used to determine whether the above switch cabinet device exists a partial discharge phenomenon; the determination unit 40 is used to determine the current partial discharge state of each of the above switch cabinet devices according to the target pulse current signal and the partial discharge early warning model, and the current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet device at the current time.

[0089] The above-mentioned switch cabinet device partial discharge phenomenon detection device of the present application comprises a collection unit, a first processing unit, a second processing unit and a determination unit, the collection unit is used to simultaneously collect pulse current signal data of a plurality of switch cabinet devices, to obtain initial pulse current signal corresponding to each of the switch cabinet devices; the first processing unit is used to pre-process the initial pulse current signal of each of the switch cabinet devices, to obtain a target pulse current signal corresponding to each of the switch cabinet devices; the second processing unit is used to establish a partial discharge early warning model, the partial discharge early warning model is used to determine whether the switch cabinet device exists a partial discharge phenomenon; the determination unit is used to determine the current partial discharge state of each of the switch cabinet devices according to the target pulse current signal and the partial discharge early warning model, and the current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet device at the current time. The device simultaneously collects and uploads the pulse current signal data of a plurality of switch cabinets in the power distribution room to the data center by using the improved centralized data collection equipment; the data center pre-processes the collected pulse current signal data and converts it into partial discharge data, at the same time, based on the actual work experience of the operation and maintenance site, a partial discharge early warning model is constructed to judge the uploaded real-time partial discharge data and output the corresponding judgment result, which realizes the remote inspection of the switch cabinet local equipment partial discharge by the operation and maintenance personnel, effectively reduces the labor cost, improves the monitoring efficiency, solves the problem that the traditional switch cabinet device partial discharge detection method can only detect one switch cabinet device at a time, cannot realize "one-to-many" simultaneous collection, and consumes a lot of human resources and has high detection cost and low efficiency.

[0090] In some examples, the pulse current signal data of all the switch cabinet devices is collected simultaneously by using the same collection device, the collection device includes a plurality of data collection interfaces, the data collection interfaces correspond to the switch cabinet devices one by one, the collection device includes an alarm function, and the alarm function of the collection device is used to send an alarm information when the partial discharge phenomenon occurs in the switch cabinet device. In this way, the pulse current signal data of multiple switch cabinets in the power distribution room can be collected simultaneously in real time, remote inspection of the partial discharge of the switch cabinet device by the operation and maintenance personnel can be realized, the labor cost is effectively reduced, and the monitoring efficiency is improved.

[0091] In some examples, the first processing unit includes a first determination module, a second determination module, and a first processing module, the first determination module is used to determine whether there is missing data in the initial pulse current signal of each switch cabinet device, the second determination module is used to determine the initial pulse current signal as the target pulse current signal corresponding to the switch cabinet device when there is no missing data in the initial pulse current signal, and the first processing module is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet device when there is missing data in the initial pulse current signal. In this way, the missing value can be accurately supplemented, the integrity of the data is ensured, and the accuracy of the subsequent partial discharge phenomenon judgment of the switch cabinet is ensured.

[0092] In some examples, the first processing module includes a construction module and a second processing module, the construction module is used to construct a forward neural network model, the neural network model is trained by using a plurality of sets of training data, each set of training data in the plurality of sets of training data includes historical pulse current signals of the switch cabinet device and historical related operation data of the switch cabinet device corresponding to the historical pulse current signals acquired in a historical time period, and the historical related operation data includes voltage values and device temperatures of the switch cabinet device in the historical time period, and the second processing module is used to predict and supplement the missing data by using the neural network model to obtain the target pulse current signal corresponding to the switch cabinet device. The missing data is predicted and supplemented by using the neural network, so that the supplemented missing data is closer to the real data, and the accuracy of the data is increased.

[0093] In this embodiment, the second processing module includes an acquisition submodule and a processing submodule. The acquisition submodule is configured to acquire a data supplement formula K=f(t, v, w), where K represents a predicted missing value, t represents a specific time period of a prediction day, v represents a voltage value of the switch cabinet equipment on the prediction day, w represents a temperature of the switch cabinet equipment on the prediction day, and f() represents a neural network model. The processing submodule is configured to predict and supplement the missing data according to the data supplement formula to obtain the target pulse current signal corresponding to the switch cabinet equipment. The neural network is used to predict and supplement the missing data, which can increase the accuracy of the data.

[0094] As an optional solution, the determination unit includes a third processing module and a fourth processing module. The third processing module is configured to analyze and calculate the target pulse current signal based on the principle of the pulse current method to obtain the apparent discharge amount corresponding to the switch cabinet equipment. The fourth processing module is configured to input the apparent discharge amount into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment. The current partial discharge state includes no partial discharge phenomenon, partial discharge phenomenon, and hidden danger of partial discharge phenomenon. In this way, the monitoring result can be prevented from being interfered by some high-frequency signals from the outside, and false alarm phenomenon can be avoided.

[0095] As an optional solution, the fourth processing module includes a third determination module, a fourth determination module, and a fifth determination module. The third determination module is configured to determine that the current partial discharge state of the switch cabinet equipment is the no partial discharge phenomenon and output the current partial discharge value of the switch cabinet equipment when the apparent discharge amount is less than a first preset value. The fourth determination module is configured to determine that the current partial discharge state of the switch cabinet equipment is the hidden danger of partial discharge phenomenon and send an early warning information when the apparent discharge amount is greater than or equal to the first preset value and less than a second preset value. The fifth determination module is configured to determine that the current partial discharge state of the switch cabinet equipment is the partial discharge phenomenon and send an alarm information when the apparent discharge amount is greater than or equal to the second preset value. By setting different alarm logics, the false alarm rate is reduced, and the alarm accuracy is improved.

[0096] The switch cabinet equipment partial discharge phenomenon detection device includes a processor and a memory. The acquisition unit and the like are stored in the memory as program units, and the corresponding functions are realized by the processor executing the program units stored in the memory. The modules are located in the same processor, or the modules are located in different processors in any combination.

[0097] The processor comprises a core, and the core retrieves corresponding program units in the memory.

[0098] The memory can comprise 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 memory (flash RAM), and the memory comprises at least one memory chip.

[0099] The embodiment of the present application provides a computer readable storage medium, and the computer readable storage medium comprises a stored program, wherein the program controls a device where the computer readable storage medium is located to perform the detection method for the partial discharge phenomenon of the switch cabinet equipment when the program is running.

[0100] Specifically, the detection method for the partial discharge phenomenon of the switch cabinet equipment comprises:

[0101] Step S201, pulse current signal data of a plurality of switch cabinet equipments are simultaneously collected to obtain initial pulse current signals corresponding to each of the switch cabinet equipments;

[0102] Specifically, first, the data acquisition equipment is used to collect pulse current data of the switch cabinet equipment in the power distribution room. The pulse current data of the switch cabinet in the power distribution room is simultaneously collected by using the improved centralized data acquisition equipment, and real-time data is transmitted to the data center through the wireless Bluetooth communication mode.

[0103] Step S202, the initial pulse current signals of each of the switch cabinet equipments are preprocessed to obtain target pulse current signals corresponding to each of the switch cabinet equipments;

[0104] Specifically, the pulse current signal data is preprocessed. First, it is judged whether there is a data missing value, if there is no missing value, the pulse current data is directly analyzed and calculated based on the principle of the pulse current method to obtain corresponding apparent discharge capacity. The apparent discharge capacity refers to that a certain charge quantity is injected at both ends of the test sample of the power equipment, so that the change amount of the end voltage of the test sample is the same as that of the end voltage when the partial discharge occurs. At this time, the charge quantity injected is called the apparent discharge capacity of the partial discharge. It should be noted that the apparent discharge capacity in the embodiment is directly obtained by the instrument equipment, and no detailed description is made.

[0105] Step S203, a partial discharge early warning model is established, and the partial discharge early warning model is used to determine whether the switch cabinet equipment has the partial discharge phenomenon;

[0106] Specifically, a partial discharge early warning model is established, data is analyzed and judged, and a judgment result is output. In the partial discharge monitoring process, some high-frequency signals from the outside world often interfere with the monitoring result, causing false alarm phenomena.

[0107] In step S204, the current partial discharge state of each switch cabinet device is determined according to the target pulse current signal and the partial discharge early warning model. The current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet device at the current time.

[0108] Specifically, by setting different alarm logic, the false alarm rate is reduced, and the alarm accuracy is improved.

[0109] Optionally, the pulse current signal data of all the switch cabinet devices is obtained by using the same collection device, the collection device includes a plurality of data collection interfaces, the data collection interfaces correspond to the switch cabinet devices one by one, the collection device includes an alarm function, and the alarm function of the collection device is used to send alarm information when the switch cabinet device has a partial discharge phenomenon.

[0110] Optionally, the initial pulse current signal of each switch cabinet device is preprocessed to obtain the target pulse current signal corresponding to each switch cabinet device, including: determining whether there is missing data in the initial pulse current signal of each switch cabinet device; in the case that there is no missing data in the initial pulse current signal, the initial pulse current signal is determined as the target pulse current signal corresponding to the switch cabinet device; in the case that there is missing data in the initial pulse current signal, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet device.

[0111] Optionally, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet device, including: constructing a forward neural network model, wherein the neural network model is trained using a plurality of sets of training data, each set of training data in the plurality of sets of training data includes historical pulse current signals of the switch cabinet device and historical related operating data of the switch cabinet device corresponding to the historical pulse current signals obtained in a historical time period, and the historical related operating data includes voltage values and device temperatures of the switch cabinet device in the historical time period; the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet device.

[0112] Optionally, the missing data is predicted and supplemented by using a neural network model to obtain the target pulse current signal corresponding to the switch cabinet equipment, including: obtaining a data supplement formula K=f(t, v, w), wherein K represents a predicted missing value, t represents a specific time period of a prediction day, v represents a voltage value of the switch cabinet equipment on the prediction day, w represents a temperature of the switch cabinet equipment on the prediction day, and f() represents a neural network model; and the missing data is predicted and supplemented according to the data supplement formula to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0113] Optionally, the current partial discharge state of each switch cabinet equipment is determined according to the target pulse current signal and the partial discharge early warning model, including: analyzing and calculating the target pulse current signal based on the principle of the pulse current method to obtain the apparent discharge quantity corresponding to the switch cabinet equipment; and inputting the apparent discharge quantity into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, wherein the current partial discharge state includes no partial discharge phenomenon, partial discharge phenomenon, and partial discharge phenomenon hidden danger.

[0114] Optionally, the apparent discharge quantity is input into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, including: in the case that the apparent discharge quantity is less than a first preset value, determining that the current partial discharge state of the switch cabinet equipment is the no partial discharge phenomenon, and outputting the current partial discharge value of the switch cabinet equipment; in the case that the apparent discharge quantity is greater than or equal to the first preset value and less than a second preset value, determining that the current partial discharge state of the switch cabinet equipment is the partial discharge phenomenon hidden danger, and issuing a warning information; and in the case that the apparent discharge quantity is greater than or equal to the second preset value, determining that the current partial discharge state of the switch cabinet equipment is the partial discharge phenomenon, and issuing an alarm information.

[0115] The embodiment of the application provides a processor used for running a program, wherein the processor is used for executing the detection method of the partial discharge phenomenon of the switch cabinet equipment when the program is running.

[0116] Specifically, the detection method of the partial discharge phenomenon of the switch cabinet equipment includes:

[0117] Step S201: Pulse current signal data of a plurality of switch cabinet equipments is collected simultaneously to obtain initial pulse current signals corresponding to the switch cabinet equipments.

[0118] Specifically, first, the pulse current data of the switch cabinet equipment in the power distribution room is collected by using a data collection device. The pulse current data of the full switch cabinet in the power distribution room is collected by using the improved centralized data collection device, and the real-time data is transmitted to the data center through the wireless Bluetooth communication mode.

[0119] Step S202, the initial pulse current signal of each of the above-mentioned switch cabinet equipment is pre-processed to obtain the target pulse current signal corresponding to each of the above-mentioned switch cabinet equipment;

[0120] Specifically, the uploaded pulse current signal data is pre-processed. First, it is judged whether there is a data missing value. If there is no missing value, the uploaded pulse current data is directly analyzed and calculated based on the principle of pulse current method to obtain the corresponding apparent discharge quantity. The "apparent discharge quantity" refers to injecting a certain amount of electric charge between the two ends of the test sample of the power equipment, so that the change of the end voltage of the test sample is the same as that when the partial discharge occurs. At this time, the amount of electric charge injected is called the apparent discharge quantity of the partial discharge. It should be noted that the apparent discharge quantity in the present embodiment is directly obtained by the instrument equipment, and will not be described in detail.

[0121] Step S203, a partial discharge early warning model is established, and the partial discharge early warning model is used to determine whether the switch cabinet equipment has a partial discharge phenomenon;

[0122] Specifically, the partial discharge early warning model is established to analyze and judge the data and output the judgment result. In the process of partial discharge monitoring, the monitoring result is often disturbed by some high-frequency signals from the outside world, causing false alarm phenomenon.

[0123] Step S204, according to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each of the above-mentioned switch cabinet equipment is determined, and the current partial discharge state represents the existence state of the partial discharge phenomenon of the switch cabinet equipment at the current time.

[0124] Specifically, by setting different alarm logic, the false alarm rate is reduced and the alarm accuracy is improved.

[0125] Optionally, the pulse current signal data of all the above-mentioned switch cabinet equipment is obtained by using the same collection device at the same time, the collection device includes a plurality of data collection interfaces, the data collection interfaces correspond to the switch cabinet equipment one by one, the collection device includes an alarm function, and the alarm function of the collection device is used to send alarm information when the switch cabinet equipment has a partial discharge phenomenon.

[0126] Optionally, the initial pulse current signal of each of the above-mentioned switch cabinet equipment is pre-processed to obtain a target pulse current signal corresponding to each of the above-mentioned switch cabinet equipment, comprising: determining whether there is missing data in the initial pulse current signal of each of the above-mentioned switch cabinet equipment; in the case that there is no missing data in the initial pulse current signal, the initial pulse current signal is determined as the target pulse current signal corresponding to the switch cabinet equipment; in the case that there is missing data in the initial pulse current signal, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0127] Optionally, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet equipment, comprising: constructing a forward neural network model, wherein the neural network model is trained using a plurality of sets of training data, each set of training data in the plurality of sets of training data includes historical pulse current signals of the switch cabinet equipment and historical related operating data of the switch cabinet equipment corresponding to the historical pulse current signals obtained in a historical time period, the historical related operating data includes voltage values and equipment temperatures of the switch cabinet equipment in the historical time period; the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0128] Optionally, the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet equipment, comprising: obtaining a data supplement formula K = f(t, v, w), wherein K represents the predicted missing value, t represents a specific time period of a prediction day, v represents a voltage value of the switch cabinet equipment on the prediction day, w represents a temperature of the switch cabinet equipment on the prediction day, and f() represents a neural network model; the missing data is predicted and supplemented according to the data supplement formula to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0129] Optionally, according to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each of the above-mentioned switch cabinet equipment is determined, comprising: analyzing and calculating the target pulse current signal based on the principle of pulse current method to obtain the apparent discharge quantity corresponding to the switch cabinet equipment; inputting the apparent discharge quantity into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, the current partial discharge state including no partial discharge phenomenon, partial discharge phenomenon, and partial discharge phenomenon hidden danger.

[0130] Optionally, the apparent discharge quantity is input into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, including: in the case that the apparent discharge quantity is less than a first preset value, determining that the current partial discharge state of the switch cabinet equipment is that no partial discharge phenomenon occurs, and outputting the current partial discharge value of the switch cabinet equipment; in the case that the apparent discharge quantity is greater than or equal to the first preset value and less than a second preset value, determining that the current partial discharge state of the switch cabinet equipment is that there is a hidden danger of partial discharge phenomenon, and issuing a warning information; in the case that the apparent discharge quantity is greater than or equal to the second preset value, determining that the current partial discharge state of the switch cabinet equipment is that the partial discharge phenomenon occurs, and issuing an alarm information.

[0131] An apparatus is provided, the apparatus comprising a processor, a memory, and a program stored on the memory and executable on the processor, the processor implementing at least the following steps when executing the program:

[0132] Step S201, pulse current signal data of a plurality of switch cabinet equipments is collected simultaneously to obtain initial pulse current signals corresponding to each of the switch cabinet equipments;

[0133] Step S202, the initial pulse current signals of each of the switch cabinet equipments are preprocessed to obtain target pulse current signals corresponding to each of the switch cabinet equipments;

[0134] Step S203, a partial discharge early warning model is established, the partial discharge early warning model being used to determine whether there is a partial discharge phenomenon in the switch cabinet equipment;

[0135] Step S204, according to the target pulse current signals and the partial discharge early warning model, a current partial discharge state of each of the switch cabinet equipments is determined, the current partial discharge state representing an existence state of the partial discharge phenomenon of the switch cabinet equipment at the current time.

[0136] The apparatus herein can be a server, a PC, a PAD, a mobile phone, etc.

[0137] Optionally, the pulse current signal data of all the switch cabinet equipments is obtained simultaneously by using a same collection apparatus, the collection apparatus comprising a plurality of data collection interfaces, the data collection interfaces corresponding to the switch cabinet equipments one by one, the collection apparatus comprising an alarm function, the alarm function of the collection apparatus being used to issue an alarm information in the case that the switch cabinet equipment has a partial discharge phenomenon.

[0138] Optionally, the initial pulse current signal of each of the above-mentioned switch cabinet equipment is pre-processed to obtain a target pulse current signal corresponding to each of the above-mentioned switch cabinet equipment, comprising: determining whether there is missing data in the initial pulse current signal of each of the above-mentioned switch cabinet equipment; in the case that there is no missing data in the initial pulse current signal, the initial pulse current signal is determined as the target pulse current signal corresponding to the switch cabinet equipment; in the case that there is missing data in the initial pulse current signal, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0139] Optionally, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet equipment, comprising: constructing a forward neural network model, wherein the neural network model is trained using a plurality of sets of training data, each set of training data in the plurality of sets of training data includes historical pulse current signals of the switch cabinet equipment and historical related operating data of the switch cabinet equipment corresponding to the historical pulse current signals obtained in a historical time period, the historical related operating data includes voltage values and equipment temperatures of the switch cabinet equipment in the historical time period; the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0140] Optionally, the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet equipment, comprising: obtaining a data supplement formula K = f(t, v, w), wherein K represents the predicted missing value, t represents a specific time period of a prediction day, v represents a voltage value of the switch cabinet equipment on the prediction day, w represents a temperature of the switch cabinet equipment on the prediction day, and f() represents a neural network model; the missing data is predicted and supplemented according to the data supplement formula to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0141] Optionally, according to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each of the above-mentioned switch cabinet equipment is determined, comprising: analyzing and calculating the target pulse current signal based on the principle of pulse current method to obtain the apparent discharge quantity corresponding to the switch cabinet equipment; inputting the apparent discharge quantity into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, the current partial discharge state including no partial discharge phenomenon, partial discharge phenomenon, and partial discharge phenomenon hidden danger.

[0142] Optionally, the apparent discharge quantity is input into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, including: in the case that the apparent discharge quantity is less than a first preset value, determining that the current partial discharge state of the switch cabinet equipment is that no partial discharge phenomenon occurs, and outputting the current partial discharge value of the switch cabinet equipment; in the case that the apparent discharge quantity is greater than or equal to the first preset value and less than a second preset value, determining that the current partial discharge state of the switch cabinet equipment is that there is a hidden danger of partial discharge phenomenon, and issuing a warning information; in the case that the apparent discharge quantity is greater than or equal to the second preset value, determining that the current partial discharge state of the switch cabinet equipment is that the partial discharge phenomenon occurs, and issuing an alarm information.

[0143] The application also provides a computer program product adapted to execute a program comprising at least the following method steps when executed on a data processing device:

[0144] Step S201, simultaneously collecting pulse current signal data of a plurality of switch cabinet equipment to obtain initial pulse current signals corresponding to each of the switch cabinet equipment;

[0145] Step S202, preprocessing the initial pulse current signals of each of the switch cabinet equipment to obtain target pulse current signals corresponding to each of the switch cabinet equipment;

[0146] Step S203, establishing a partial discharge early warning model, the partial discharge early warning model being used to determine whether the switch cabinet equipment has a partial discharge phenomenon;

[0147] Step S204, determining a current partial discharge state of each of the switch cabinet equipment according to the target pulse current signals and the partial discharge early warning model, the current partial discharge state representing an existence state of the partial discharge phenomenon of the switch cabinet equipment at the current time.

[0148] Optionally, the pulse current signal data of all the switch cabinet equipment is simultaneously collected by using a same collection device, the collection device comprising a plurality of data collection interfaces, the data collection interfaces corresponding to the switch cabinet equipment one by one, the collection device comprising an alarm function, the alarm function of the collection device being used to issue an alarm information in the case that the switch cabinet equipment has a partial discharge phenomenon.

[0149] Optionally, the initial pulse current signal of each of the above-mentioned switch cabinet equipment is pre-processed to obtain a target pulse current signal corresponding to each of the above-mentioned switch cabinet equipment, comprising: determining whether there is missing data in the initial pulse current signal of each of the above-mentioned switch cabinet equipment; in the case that there is no missing data in the initial pulse current signal, the initial pulse current signal is determined as the target pulse current signal corresponding to the switch cabinet equipment; in the case that there is missing data in the initial pulse current signal, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0150] Optionally, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet equipment, comprising: constructing a forward neural network model, wherein the neural network model is trained using a plurality of sets of training data, each set of training data in the plurality of sets of training data comprising historical pulse current signals of the switch cabinet equipment and historical related operating data of the switch cabinet equipment corresponding to the historical pulse current signals obtained in a historical time period, the historical related operating data comprising voltage values and equipment temperatures of the switch cabinet equipment in the historical time period; the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0151] Optionally, the neural network model is used to predict and supplement the missing data to obtain the target pulse current signal corresponding to the switch cabinet equipment, comprising: obtaining a data supplement formula K = f(t, v, w), wherein K represents the predicted missing value, t represents a specific time period of a prediction day, v represents a voltage value of the switch cabinet equipment on the prediction day, w represents a temperature of the switch cabinet equipment on the prediction day, and f() represents a neural network model; the missing data is predicted and supplemented according to the data supplement formula to obtain the target pulse current signal corresponding to the switch cabinet equipment.

[0152] Optionally, according to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each of the above-mentioned switch cabinet equipment is determined, comprising: analyzing and calculating the target pulse current signal based on the principle of pulse current method to obtain the apparent discharge quantity corresponding to the switch cabinet equipment; inputting the apparent discharge quantity into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, the current partial discharge state comprising no partial discharge phenomenon, partial discharge phenomenon, and partial discharge phenomenon hidden danger.

[0153] Optionally, the apparent discharge quantity is input into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet equipment, including: in the case that the apparent discharge quantity is less than a first preset value, determining that the current partial discharge state of the switch cabinet equipment is that no partial discharge phenomenon occurs, and outputting the current partial discharge value of the switch cabinet equipment; in the case that the apparent discharge quantity is greater than or equal to the first preset value and less than a second preset value, determining that the current partial discharge state of the switch cabinet equipment is that there is a hidden danger of partial discharge phenomenon, and issuing a warning information; in the case that the apparent discharge quantity is greater than or equal to the second preset value, determining that the current partial discharge state of the switch cabinet equipment is that the partial discharge phenomenon occurs, and issuing an alarm information.

[0154] It is apparent that those skilled in the art should understand that the modules or steps of the present application described above can be realized by using general computing devices, which can be centralized on a single computing device or distributed on a network composed of multiple computing devices, and can be realized by using program codes executable by the computing devices, so that they can be stored in storage devices and executed by the computing devices, and in some cases, the steps shown or described can be executed in different orders, or they can be manufactured into individual integrated circuit modules or a single integrated circuit module. Therefore, the present application is not limited to any specific combination of hardware and software.

[0155] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can be in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0156] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The devices that realize the functions specified in one block or multiple blocks.

[0157] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0159] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0160] The memory can include non-persistent memory and / or volatile memory, such as a random access memory (RAM) including a cache area for the temporary storage of data. The memory can also include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), flash memory, or a combination of non-volatile memories in different forms. The memory is an example of computer readable storage media.

[0161] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as 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 programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassettes, magnetic disks storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0162] It should also be noted that the terms "comprising", "comprising" or any other variant thereof are intended to cover non-exclusive inclusions, such that processes, methods, articles or devices that comprise a list of elements do not only include those elements, but also other elements not explicitly listed, or other elements inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the phrase "comprising a" does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0163] From the above description, it can be seen that the above-mentioned embodiments of the present application achieve the following technical effects:

[0164] 1) The above-mentioned switch cabinet equipment partial discharge detection method of the present application first simultaneously collects pulse current signal data of multiple switch cabinet equipment, obtains initial pulse current signal corresponding to each switch cabinet equipment; pre-processes the initial pulse current signal of each switch cabinet equipment to obtain the target pulse current signal corresponding to each switch cabinet equipment; establishes a partial discharge early warning model, which is used to determine whether the switch cabinet equipment has a partial discharge phenomenon; according to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each switch cabinet equipment is determined, which represents the existence state of the partial discharge phenomenon of the switch cabinet equipment at the current time. This method uses the improved centralized data collection equipment to simultaneously collect the pulse current signal data of multiple switch cabinets in the power distribution room in real time, and uploads it to the data center; the data center pre-processes the collected pulse current signal data and converts it into partial discharge data, at the same time, based on the actual work experience of the operation and maintenance site, a partial discharge early warning model is constructed to judge the uploaded real-time partial discharge data and output the corresponding judgment result. This method realizes remote inspection of switch cabinet partial discharge by operation and maintenance personnel, effectively reduces labor cost, improves monitoring efficiency, solves the problem that the traditional switch cabinet equipment partial discharge detection method can only detect one switch cabinet equipment at a time, cannot realize "one-to-many" simultaneous collection, and has large labor resource consumption, high detection cost and low efficiency.

[0165] 2) The detection system of the above-mentioned partial discharge phenomenon of the switch cabinet equipment of the application uses the improved centralized data acquisition equipment to simultaneously collect pulse current data of the full switch cabinet of the power distribution room, and transmits real-time data to the data center through wireless Bluetooth communication. Not only is the data acquisition interface of the traditional partial pulse current data acquisition equipment of the switch cabinet of the power distribution room improved, but also the external data acquisition interface is expanded, which can be customized according to the actual needs on site, and active alarm uploading is also set. Once the pulse current data collected by a certain switch cabinet reaches the preset alarm value, it will be uploaded immediately. This method realizes remote inspection of the partial discharge of the switch cabinet by the operation and maintenance personnel, effectively reduces the labor cost, improves the monitoring efficiency, solves the problem that the traditional partial discharge detection method of the switch cabinet equipment can only detect one switch cabinet equipment at a time, cannot realize "one-to-many" simultaneous collection, and consumes a lot of human resources, has high detection cost and low efficiency.

[0166] The above only describes the preferred embodiments of the application and is not intended to limit the application. Those skilled in the art can make various modifications and changes to the application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the application shall be included in the protection scope of the application.

Claims

1. A method for detecting partial discharge phenomena of a switchgear device, characterized in that The method comprises the following steps: Collecting pulse current signal data of multiple switch cabinet devices simultaneously to obtain initial pulse current signal corresponding to each switch cabinet device; Pretreating the initial pulse current signal of each switch cabinet device to obtain target pulse current signal corresponding to each switch cabinet device; Establishing a partial discharge early warning model, which is used to determine whether there is a partial discharge phenomenon in the switch cabinet device; According to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each switch cabinet device is determined, which represents the existence state of the partial discharge phenomenon of the switch cabinet device at the current time; Pretreating the initial pulse current signal of each switch cabinet device to obtain target pulse current signal corresponding to each switch cabinet device, comprising: Determine whether there is missing data in the initial pulse current signal of each switch cabinet device; In the case where there is no missing data in the initial pulse current signal, the initial pulse current signal is determined as the target pulse current signal corresponding to the switch cabinet device; In the case where there is missing data in the initial pulse current signal, a forward neural network model is constructed, wherein the neural network model is trained using multiple sets of training data, each set of training data includes historical pulse current signal and historical related operating data of the switch cabinet device corresponding to the historical pulse current signal obtained in a historical time period, the historical related operating data includes voltage value and device temperature of the switch cabinet device in the historical time period; acquisition data supplement formula wherein, denotes a predicted missing value, denotes a specific time period of a prediction day, denotes a voltage value of the switchgear device on the prediction day, denotes a temperature of the switchgear device on the prediction day, denotes a neural network model; According to the data supplement formula, the missing data is predicted and supplemented to obtain the target pulse current signal corresponding to the switch cabinet device.

2. The method of claim 1, wherein, All the pulse current signal data of the switch cabinet devices are collected simultaneously by using the same collection device, the collection device includes multiple data collection interfaces, the data collection interfaces correspond to the switch cabinet devices one by one, the collection device includes an alarm function, and the alarm function of the collection device is used to send alarm information when the switch cabinet device has a partial discharge phenomenon.

3. The method of claim 1, wherein, According to the target pulse current signal and the partial discharge early warning model, the current partial discharge state of each switch cabinet device is determined, comprising: Based on the principle of pulse current method, the target pulse current signal is analyzed and calculated to obtain the apparent discharge quantity corresponding to the switch cabinet device; The apparent discharge quantity is input into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet device, which includes no partial discharge phenomenon, partial discharge phenomenon and partial discharge phenomenon hidden danger.

4. The method of claim 3, wherein, The apparent discharge quantity is input into the partial discharge early warning model to obtain the current partial discharge state of the switch cabinet device, comprising: In the case where the apparent discharge quantity is less than a first preset value, it is determined that the current partial discharge state of the switch cabinet device is the no partial discharge phenomenon, and the current partial discharge value of the switch cabinet device is output. In a case where the apparent discharge quantity is greater than or equal to the first preset value and less than a second preset value, it is determined that the current partial discharge state of the switch cabinet equipment is that there is a hidden danger of partial discharge phenomenon, and a pre-warning information is sent out; In a case where the apparent discharge quantity is greater than or equal to the second preset value, it is determined that the current partial discharge state of the switch cabinet equipment is that there is a partial discharge phenomenon, and an alarm information is sent out.

5. A system for detecting partial discharge phenomena in switchgear equipment, characterized by The method comprises: A detection device for detecting a partial discharge phenomenon of a switch cabinet equipment, which is configured to execute the method for detecting a partial discharge phenomenon of a switch cabinet equipment according to any one of claims 1 to 4; A collection device, which is wirelessly connected to the detection device for detecting a partial discharge phenomenon of a switch cabinet equipment through Bluetooth.

6. A computer readable storage medium characterized by, The computer readable storage medium comprises a stored program, wherein the program controls the device where the computer readable storage medium is located to execute the method for detecting a partial discharge phenomenon of a switch cabinet equipment according to any one of claims 1 to 4 when the program is running.

7. An electronic device, comprising: The method comprises: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs comprise a program for executing the method for detecting a partial discharge phenomenon of a switch cabinet equipment according to any one of claims 1 to 4.

Images