Partial discharge identification method and device for gas insulated switchgear, and storage medium
Through the method of synchronous acquisition and feature extraction of multi-sensors, the locally distributed signals of gas insulated switch equipment are identified, which solves the reliability and accuracy problems of a single detection method in complex electromagnetic environments, and achieves more efficient locally distributed signal detection.
Patent Information
- Application Number
- CN202411840982.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-13
- Publication Date
- 2025-03-14
AI Technical Summary
In complex electromagnetic environments, a single detection method has low reliability and accuracy in detecting locally released signals of gas insulated switchgears.
By deploying multiple sensors (such as ultra-high frequency, ultrasonic and fiber optic sensors) and calling these sensors to synchronize the relevant original sensing signals, extracting the original sensing features, performing filtering and fusion, obtaining multimodal sensing features, and finally identifying the type of local discharge signals.
It improves the accuracy and reliability of detecting locally distributed signals, is suitable for complex electromagnetic environments, and supports preventive maintenance of power systems.
Smart Images
Figure CN119622387A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of electric power technology, and in particular to a partial discharge identification method, device and storage medium for a gas insulated switchgear. Background Art
[0002] In power systems, Gas Insulated Switchgear (GIS) has been widely used due to its high reliability, low maintenance requirements and good resistance to environmental interference.
[0003] Insulating materials inside gas-insulated switchgear may cause partial discharge (PD) during long-term operation, which will affect the safe operation of the gas-insulated switchgear.
[0004] In order to prevent the gas-insulated switchgear from malfunctioning, the partial discharge signal (ie, partial discharge signal) generated in the gas-insulated switchgear is usually detected in real time.
[0005] At present, the methods for detecting partial discharge signals of gas-insulated switchgear mainly include ultra-high frequency (UHF) method, ultrasonic detection method, optical fiber sensing method and electromagnetic wave time domain reflection (TDR) method.
[0006] However, each individual detection method has obvious advantages and disadvantages. For example, the UHF method has strong anti-interference ability but requires high sensor layout, the ultrasonic method has high sensitivity but is easily interfered by environmental noise, the fiber optic sensing method has high sensitivity but high cost, and the TDR method has high positioning accuracy but complex equipment.
[0007] In a complex electromagnetic environment, the reliability and accuracy of detecting partial discharge signals using a single detection method are low. Summary of the invention
[0008] In view of this, the present invention provides a partial discharge identification method, device and storage medium for a gas insulated switchgear, so as to improve the reliability and accuracy of detecting partial discharge signals.
[0009] A first aspect of the present invention provides a method for identifying partial discharge of a gas insulated switchgear, comprising:
[0010] Determine a gas-insulated switchgear; the gas-insulated switchgear is deployed with a plurality of sensors;
[0011] Calling a plurality of the sensors to synchronously collect a plurality of original sensing signals related to partial discharge signals from the gas insulated switchgear;
[0012] Extracting a plurality of original perception features from a plurality of the original perception signals according to the type of the sensor;
[0013] Filtering and fusing the multiple original perception features to obtain multimodal perception features;
[0014] The type of the partial discharge signal in the gas insulated switchgear is identified based on the multimodal sensing feature.
[0015] A second aspect of the present invention provides a partial discharge identification device for a gas insulated switchgear, comprising:
[0016] A device determination module, used to determine a gas-insulated switchgear; the gas-insulated switchgear is deployed with a variety of sensors;
[0017] An original sensing signal acquisition module, used for calling a plurality of the sensors to synchronously acquire a plurality of original sensing signals related to partial discharge signals from the gas insulated switchgear;
[0018] An original perception feature extraction module, used for extracting a plurality of original perception features from a plurality of the original perception signals according to the type of the sensor;
[0019] A multimodal perception feature fusion module, used for filtering and fusing the multiple original perception features to obtain a multimodal perception feature;
[0020] A partial discharge type identification module is used to identify the type of partial discharge signal in the gas insulated switchgear based on the multimodal sensing feature.
[0021] A third aspect of the present invention provides an electronic device, the electronic device comprising:
[0022] at least one processor; and
[0023] a memory communicatively connected to the at least one processor; wherein,
[0024] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the partial discharge identification method for gas insulated switchgear as described in the first aspect above.
[0025] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the partial discharge identification method for a gas-insulated switchgear as described in the first aspect above.
[0026] A fifth aspect of the present invention provides a computer program product, the computer program product comprising a computer program, and when the computer program is executed by a processor, the method for identifying partial discharge of a gas insulated switchgear as described in the first aspect above is implemented.
[0027] In this embodiment, a gas insulated switchgear is determined; a plurality of sensors are deployed in the gas insulated switchgear; a plurality of sensors are called to synchronously collect a plurality of original sensing signals related to partial discharge signals from the gas insulated switchgear; a plurality of original sensing features are extracted from the plurality of original sensing signals according to the type of sensor; a plurality of original sensing features are filtered and fused to obtain multimodal sensing features; and the type of partial discharge signal in the gas insulated switchgear is identified according to the multimodal sensing features. This embodiment combines a plurality of sensors as signal sources, and increases the signal quality through the complementarity of multi-source signals, thereby effectively improving the accuracy and reliability of detecting partial discharge signals, and is suitable for detecting partial discharge signals in various complex electromagnetic environments, and provides strong support for the preventive maintenance of various electrical equipment in the power system.
[0028] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0030] Figure 1 This is a flow chart of a partial discharge identification method for a gas insulated switchgear provided in Embodiment 1 of the present invention.
[0031] Figure 2 It is a structural schematic diagram of a partial discharge identification device for a gas insulated switchgear provided in Embodiment 2 of the present invention.
[0032] Figure 3 It is a structural schematic diagram of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION
[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.
[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can cover sequential implementations other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0035] Embodiment 1
[0036] See also Figure 1 , shows a flow chart of a partial discharge identification method for a gas insulated switchgear provided in Embodiment 1 of the present invention, the method can be executed by a partial discharge identification device for a gas insulated switchgear, the partial discharge identification device for a gas insulated switchgear can be implemented in the form of hardware and / or software, and the partial discharge identification device for a gas insulated switchgear can be configured in an electronic device. Figure 1 As shown, the method includes:
[0037] Step 101: Determine the gas insulated switchgear.
[0038] In this embodiment, the gas-insulated switchgear is deployed with a variety of different sensors, and the various sensors can monitor the operating status of the gas-insulated switchgear from multiple dimensions, thereby improving the comprehensiveness of the monitoring.
[0039] Exemplarily, the types of sensors include ultra high frequency (UHF) sensors, ultrasonic sensors, and fiber optic sensors.
[0040] The operating frequency range of UHF sensors is between 300MHz and 3GHz. They are placed near key nodes of gas-insulated switchgear, such as busbar joints, circuit breakers and disconnectors. The installation location of UHF sensors should ensure direct line of sight with the parts of gas-insulated switchgear where partial discharge may occur, so as to improve the signal reception strength. UHF sensors can be connected to computing equipment via coaxial cables.
[0041] The operating frequency range of ultrasonic sensors is between 20kHz and 300kHz. They are placed on the outer shell surface of gas-insulated switchgear, and a special coupling medium is used between the two to ensure that the sound wave signal can be effectively transmitted to the ultrasonic sensor. The location of the ultrasonic sensor should be as far away from strong noise sources as possible and as close as possible to the part of the gas-insulated switchgear where partial discharge may occur.
[0042] The fiber optic sensor is as sensitive as possible to detect small changes in heat or vibration. It is placed inside or near the gas-insulated switchgear, especially in high-temperature and high-vibration areas such as switches and transformers. The sensor is connected to the computing device through an optical fiber network.
[0043] Step 102: Call multiple sensors to synchronously collect multiple original sensing signals related to partial discharge signals from the gas insulated switchgear.
[0044] In this embodiment, multiple sensors are called to synchronously collect multiple original sensing signals related to partial discharge signals from the gas insulated switchgear at a high sampling rate (such as above 10 MHz).
[0045] Exemplarily, the types of sensors include ultra-high frequency sensors, ultrasonic sensors and optical fiber sensors. Then, the ultra-high frequency sensors, ultrasonic sensors and optical fiber sensors can be called to synchronously collect a variety of original sensing signals related to partial discharge signals from the gas-insulated switchgear.
[0046] Furthermore, an ultra-high frequency sensor is called to collect electromagnetic wave signals (i.e., original perception signals) related to local discharge signals of the gas-insulated switchgear, an ultrasonic sensor is called to collect sound wave signals (i.e., original perception signals) related to local discharge signals of the gas-insulated switchgear, and an optical fiber sensor is called to collect tiny heat change signals or vibration signals (i.e., original perception signals) related to local discharge signals of the gas-insulated switchgear.
[0047] Step 103: extract multiple original perception features from multiple original perception signals according to the type of sensor.
[0048] In this embodiment, the characteristics of sensors of different types are different, and the characteristics of the original perception signals collected by them are also different. Therefore, suitable feature engineering can be constructed for various original perception signals according to the types of sensors, and various original perception features can be extracted from the various original perception signals.
[0049] In a specific implementation, the original perception signal may be preprocessed according to the type of sensor to obtain a target perception signal, so as to improve the quality of the target perception signal.
[0050] Exemplarily, the preprocessing includes at least one of an amplification process, a filtering process, and an analog-to-digital conversion process.
[0051] Among them, for the amplification processing, the original sensing signal collected by the optical fiber sensor is enhanced in signal strength through a matching circuit.
[0052] For filtering processing, a denoising algorithm based on wavelet transform and an adaptive filtering algorithm are usually included to eliminate high-frequency noise and low-frequency baseline drift.
[0053] Furthermore, the original sensing signal collected by the UHF sensor is filtered by a bandpass filter to eliminate low-frequency interference.
[0054] The original sensing signal collected by the ultrasonic sensor is filtered by a high-pass filter to eliminate low-frequency noise.
[0055] Of course, the above-mentioned sensors and their preprocessing methods are only examples. When implementing this embodiment, other sensors and their preprocessing methods can be set according to actual conditions, and this embodiment does not limit this. In addition, in addition to the above-mentioned sensors and their preprocessing methods, those skilled in the art can also use other sensors and their preprocessing methods according to actual needs, and this embodiment does not limit this.
[0056] If the preprocessing is completed, the appropriate feature algorithm can be selected according to the type of sensor to extract the original perception features from the target perception signal.
[0057] In a specific implementation, if the type of the sensor is an ultra-high frequency sensor, the original perception features on the frequency spectrum are extracted from the target perception signal.
[0058] If the sensor type is an ultrasonic sensor, the original perception features in time and frequency are extracted from the target perception signal.
[0059] If the sensor is a fiber optic sensor, differential detection is performed on the target sensing signal to obtain an original sensing feature representing the change in temperature or stress.
[0060] Step 104: Filter and fuse the multiple original perception features to obtain multimodal perception features.
[0061] In the specific implementation, multiple original perception features are time synchronized, and the synchronized multiple original perception features are filtered and fused to obtain multimodal perception features, realize joint signal processing of multiple sensors, and improve the detection accuracy of partial discharge signals through the complementarity of multi-source data.
[0062] In one embodiment of the present invention, Kalman filtering may be performed on a plurality of original perceptual features to fuse them into multimodal perceptual features. Then, in this embodiment, step 104 may include the following steps:
[0063] Step 1041: Collect parameters related to the partial discharge signal of the gas insulated switchgear.
[0064] In this embodiment, various parameters related to the partial discharge signal can be collected from the gas insulated switchgear itself at various times.
[0065] Exemplarily, the parameters include discharge intensity, power, frequency, and discharge position (three-dimensional coordinates).
[0066] In this example, the parameters are expressed in matrix form as:
[0067]
[0068] Among them, x k is the parameter at time k, I k is the discharge intensity at time k, P k is the power at time k, f k is the frequency at time k, (x k ,y k ,z k ) is the discharge position at time k
[0069] Step 1042: construct a state transfer equation for the gas insulated switchgear with the parameter being the state vector of the gas insulated switchgear.
[0070] In Kalman filtering, the operating characteristics of the gas-insulated switchgear are used to establish a suitable state space model for the gas-insulated switchgear, wherein the state space model includes a state transfer equation and an observation equation.
[0071] In this embodiment, the parameters related to the partial discharge signal in the gas insulated switchgear are set as the state vector of the gas insulated switchgear, and the state vector is used to construct a state transfer equation for the gas insulated switchgear.
[0072] In the specific implementation, the state transfer equation is expressed as:
[0073] x k =Ax k-1 +Bu k +w k
[0074] Among them, x k is the state vector of the gas-insulated switchgear at time k (i.e., the parameters related to the partial discharge signal in the gas-insulated switchgear), x k is the state vector of the gas-insulated switchgear at time k-1 (i.e., the parameters related to the partial discharge signal in the gas-insulated switchgear), u k is the control input vector at time k, w k is the transfer noise at time k, A is the state transfer matrix, and B is the control input matrix.
[0075] Furthermore, w k Set it to zero mean, Gaussian white noise, and the covariance matrix is Q.
[0076] Assuming that the partial discharge signal changes steadily in a short period of time, a simple identity model can be used, A=I, B=0.
[0077] Step 1043: Use multiple sensors as independent observation sources and construct observation equations for the gas-insulated switchgear based on multiple original perception features.
[0078] In this embodiment, in a multi-sensor system, each sensor can be regarded as an independent observation source, and an observation equation is constructed for the gas insulated switchgear based on a variety of original perception features.
[0079] Then, the observation equation can be expressed as:
[0080] z k =H1x k +v 1,k +H2x k +v 2,k +…+H m x k +v m,k
[0081] Among them, z k is the observation vector at time k, m is the number of sensors, and sensor i has an independent observation matrix H i and noise v i,k .
[0082] To simplify the calculation, the observation data of all sensors can be combined into a joint observation vector. In this case, the observation equation is expressed as:
[0083] z k =Hx k +v k
[0084] Among them, z k is the multiple original perceptual features observed at time k, x k is the state vector of the gas-insulated switchgear at time k, H is the total observation matrix formed by stacking the observation matrices of multiple sensors, v k It is the total noise signal formed by the noise signals observed by each sensor at time k.
[0085] Among them, v k The covariance matrix of is the diagonal matrix of R. The noise characteristics of each sensor are different. The covariance matrix of each sensor can be determined according to the performance of the actual sensor and experimental data, and v k The covariance equation in describes the correlation between multiple sensors.
[0086] Step 1044: Update the state transfer equation according to the observation equation to generate multimodal perception features.
[0087] In this embodiment, the observation equation can be used to continuously iteratively update the state transfer equation, thereby generating multimodal perception features.
[0088] In practical applications, iterative operations include:
[0089] 1. Initialization:
[0090] Initial state estimation and the initial error covariance matrix P0.
[0091] 2. Prediction steps:
[0092] ① Status prediction:
[0093] ② Error covariance prediction:
[0094] 3. Update steps:
[0095] ① Kalman gain calculation: K k =P k|k-1 H T ( HP k|k-1 H T +R ) -1 ;
[0096] ②Status update:
[0097] ③ Error covariance update: P k|k =(IK k H)P k|k-1 .
[0098] Step 105: Identify the type of partial discharge signal in the gas insulated switchgear based on the multimodal sensing features.
[0099] In this embodiment, a classification operation may be performed based on multimodal sensing features to identify the type of partial discharge signal in the gas insulated switchgear.
[0100] In a specific implementation, K-means and other algorithms can be used to cluster the historical multimodal perception features to obtain multiple clusters, each cluster representing the type of local discharge signal, and each cluster has a center point, which is a representative of the multimodal perception features in the cluster.
[0101] Then, multiple clusters representing the types of partial discharge signals can be determined, and the distances between the multimodal perception features and each center point can be calculated using algorithms such as Euclidean distance. The distances between the multimodal perception features and each center point can be compared to screen out the cluster with the smallest distance, and determine that the partial discharge signal of the gas-insulated switchgear belongs to the type represented by the cluster with the smallest distance.
[0102] In this embodiment, a gas insulated switchgear is determined; a plurality of sensors are deployed in the gas insulated switchgear; a plurality of sensors are called to synchronously collect a plurality of original sensing signals related to partial discharge signals from the gas insulated switchgear; a plurality of original sensing features are extracted from the plurality of original sensing signals according to the type of sensor; a plurality of original sensing features are filtered and fused to obtain multimodal sensing features; and the type of partial discharge signal in the gas insulated switchgear is identified according to the multimodal sensing features. This embodiment combines a plurality of sensors as signal sources, and increases the signal quality through the complementarity of multi-source signals, thereby effectively improving the accuracy and reliability of detecting partial discharge signals, and is suitable for detecting partial discharge signals in various complex electromagnetic environments, and provides strong support for the preventive maintenance of various electrical equipment in the power system.
[0103] Embodiment 2
[0104] See also Figure 2 , shows a schematic diagram of the structure of a partial discharge identification device for a gas insulated switchgear provided in Embodiment 2 of the present invention. Figure 2 As shown, the device comprises:
[0105] The device determination module 201 is used to determine the gas insulated switchgear; the gas insulated switchgear is deployed with multiple sensors;
[0106] The original sensing signal acquisition module 202 is used to call a plurality of sensors to synchronously acquire a plurality of original sensing signals related to partial discharge signals from the gas insulated switchgear;
[0107] An original perception feature extraction module 203, configured to extract a plurality of original perception features from a plurality of the original perception signals according to the type of the sensor;
[0108] A multimodal perception feature fusion module 204 is used to filter and fuse the multiple original perception features to obtain a multimodal perception feature;
[0109] The partial discharge type identification module 205 is used to identify the type of partial discharge signal in the gas insulated switchgear according to the multimodal sensing feature.
[0110] In one embodiment of the present invention, the sensor includes an ultra-high frequency sensor, an ultrasonic sensor and an optical fiber sensor.
[0111] In one embodiment of the present invention, the original perceptual feature extraction module 203 includes:
[0112] An adaptive preprocessing module, used to perform preprocessing on the original perception signal according to the type of the sensor to obtain a target perception signal;
[0113] The adaptive feature extraction module is used to extract original perception features from the target perception signal according to the type of the sensor.
[0114] In one embodiment of the present invention, the preprocessing includes at least one of amplification processing, filtering processing and analog-to-digital conversion processing;
[0115] The adaptive feature extraction module comprises:
[0116] An ultra-high frequency processing module, configured to extract original perception features on a frequency spectrum from the target perception signal if the sensor is an ultra-high frequency sensor;
[0117] an ultrasonic processing module, configured to extract original perception features in time and frequency from the target perception signal if the sensor is an ultrasonic sensor;
[0118] The differential detection execution module is used to perform differential detection on the target sensing signal if the sensor is a fiber optic sensor, so as to obtain an original sensing feature representing a change in temperature or stress.
[0119] In one embodiment of the present invention, the multimodal perception feature fusion module 204 includes:
[0120] A partial discharge parameter acquisition module, used for acquiring parameters related to the partial discharge signal of the gas insulated switchgear;
[0121] A state transfer equation construction module, used to construct a state transfer equation for the gas insulated switchgear by taking the parameter as the state vector of the gas insulated switchgear;
[0122] An observation equation construction module, used to use the multiple sensors as independent observation sources and construct observation equations for the gas insulated switchgear according to the multiple original sensing features;
[0123] An equation updating module is used to update the state transfer equation according to the observation equation to generate multimodal perception features.
[0124] In one embodiment of the present invention, the parameters include discharge intensity, power, frequency, and discharge position.
[0125] In one embodiment of the present invention, the state transfer equation is expressed as:
[0126] x k =Ax k-1 +Bu k +w k
[0127] Among them, x k is the state vector of the gas insulated switchgear at time k, x k is the state vector of the gas insulated switchgear at time k-1, u k is the control input vector at time k, w k is the transfer noise at time k, A is the state transfer matrix, and B is the control input matrix;
[0128] The observation equation is expressed as:
[0129] z k =Hx k +v k
[0130] Among them, z k The multiple original perceptual features observed at time k, x k is the state vector of the gas-insulated switchgear at time k, H is the total observation matrix formed by stacking the observation matrices of multiple sensors, v k is the total noise signal formed by the noise signals observed by each sensor at time k, v k The covariance equation in characterizes the correlation between the various sensors.
[0131] In one embodiment of the present invention, the partial discharge type identification module 205 includes:
[0132] A cluster determination module, used to determine a plurality of clusters representing the type of partial discharge signals; each of the clusters has a center point;
[0133] A distance calculation module, used to calculate the distance between the multimodal perception feature and each of the center points;
[0134] The partial discharge type determination module is used to determine whether the partial discharge signal of the gas-insulated switchgear belongs to the type represented by the cluster with the smallest distance.
[0135] The partial discharge identification device for gas insulated switchgear provided in an embodiment of the present invention can execute the partial discharge identification method for gas insulated switchgear provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the partial discharge identification method for gas insulated switchgear.
[0136] Embodiment 3
[0137] See also Figure 3, showing a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.
[0138] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0139] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.
[0140] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the partial discharge identification method of the gas insulated switchgear.
[0141] In some embodiments, the partial discharge identification method of the gas insulated switchgear can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the partial discharge identification method of the gas insulated switchgear described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the partial discharge identification method of the gas insulated switchgear in any other appropriate manner (for example, by means of firmware).
[0142] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0143] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0144] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0145] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).
[0146] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.
[0147] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.
[0148] Embodiment 4
[0149] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method for identifying partial discharge of a gas insulated switchgear provided in any embodiment of the present invention is implemented.
[0150] In the process of implementation, the computer program product can be written in one or more programming languages or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).
[0151] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.
[0152] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A method for identifying partial discharge of a gas insulated switchgear, characterized in that: include: Determine a gas-insulated switchgear; the gas-insulated switchgear is deployed with a plurality of sensors; Invoking a plurality of the sensors to synchronously collect a plurality of original sensing signals related to partial discharge signals from the gas insulated switchgear; Extracting a plurality of original perception features from a plurality of the original perception signals according to the type of the sensor; Filtering and fusing the multiple original perception features to obtain multimodal perception features; The type of the partial discharge signal in the gas insulated switchgear is identified based on the multimodal sensing feature.
2. The method according to claim 1, characterized in that The sensors include ultra-high frequency sensors, ultrasonic sensors and optical fiber sensors.
3. The method according to claim 1, characterized in that The extracting a plurality of original perception features from a plurality of the original perception signals according to the type of the sensor comprises: Preprocessing the original sensing signal according to the type of the sensor to obtain a target sensing signal; Extracting original perception features from the target perception signal according to the type of the sensor.
4. The method according to claim 3, characterized in that The preprocessing includes at least one of amplification processing, filtering processing and analog-to-digital conversion processing; The extracting original perception features from the target perception signal according to the type of the sensor includes: If the sensor is an ultra-high frequency sensor, extracting original perception features on the frequency spectrum of the target perception signal; If the sensor is an ultrasonic sensor, extracting original perception features in time and frequency from the target perception signal; If the sensor is a fiber optic sensor, differential detection is performed on the target sensing signal to obtain an original sensing feature representing a change in temperature or stress.
5. The method according to claim 1, characterized in that The filtering and fusing of the multiple original perception features to obtain multimodal perception features includes: Collecting parameters related to the partial discharge signal of the gas insulated switchgear; Taking the parameter as the state vector of the gas insulated switchgear, constructing a state transfer equation for the gas insulated switchgear; Taking the multiple sensors as independent observation sources, constructing observation equations for the gas insulated switchgear according to the multiple original sensing features; The state transfer equation is updated according to the observation equation to generate multimodal perception features.
6. The method according to claim 5, characterized in that The parameters include discharge intensity, power, frequency, and discharge position.
7. The method according to claim 5, characterized in that The state transfer equation is expressed as: x k =Ax k-1 +Bu k +w k Among them, x k is the state vector of the gas insulated switchgear at time k, x k is the state vector of the gas insulated switchgear at time k-1, u k is the control input vector at time k, w k is the transfer noise at time k, A is the state transfer matrix, and B is the control input matrix; The observation equation is expressed as: z k =Hx k +v k Among them, z k The multiple original perceptual features observed at time k, x k is the state vector of the gas-insulated switchgear at time k, H is the total observation matrix formed by stacking the observation matrices of multiple sensors, v k is the total noise signal formed by the noise signals observed by each sensor at time k, v k The covariance equation in characterizes the correlation between the various sensors.
8. The method according to any one of claims 1 to 7, characterized in that The identifying the type of the partial discharge signal in the gas insulated switchgear according to the multimodal sensing feature comprises: Determine a plurality of clusters representing the type of partial discharge signals; each of the clusters has a center point; Calculating the distance between the multimodal perception feature and each of the central points; It is determined that the partial discharge signal of the gas insulated switchgear belongs to the type of the cluster representation with the smallest distance.
9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the partial discharge identification method for gas insulated switchgear according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for identifying partial discharge of a gas-insulated switchgear according to any one of claims 1 to 8 is implemented.