Method and device for partial discharge detection in edge cloud cooperation

Abstract

The edge cloud cooperative partial discharge detection method and device provided by the disclosure belong to the field of partial discharge monitoring, and the method comprises the following steps: a first edge partial discharge detection device judges whether there is a partial discharge phenomenon in the partial discharge data, and sends an edge partial discharge detection request to a second edge partial discharge detection device when there is no partial discharge phenomenon; the feedback result of the second edge partial discharge detection device is judged, and a cloud end partial discharge detection device is sent when the feedback result is no partial discharge phenomenon; the feedback result of the cloud end partial discharge detection device is obtained, and the partial discharge detection is executed according to the feedback result. The method cooperates with the cloud to detect the partial discharge, fully utilizes the advantages of edge partial discharge detection and cloud end partial discharge detection, and improves the efficiency of partial discharge detection.

Description

Technical Field

[0001] This application relates to the field of partial discharge monitoring, and in particular to a method and apparatus for partial discharge detection using edge-cloud collaboration. Background Technology

[0002] Edge computing can move data processing, storage, and computing power from the cloud to edge nodes closer to the data source, thereby reducing latency, saving bandwidth, and improving data privacy.

[0003] With the development of partial discharge detection, edge computing-based partial discharge detection has a promising application prospect. However, edge computing has limited processing power, and the accuracy of the artificial intelligence models it can support is usually weaker than that of the cloud. How to perform partial discharge detection based on edge-cloud collaboration has become a problem that needs to be solved. Summary of the Invention

[0004] In view of this, this application proposes a method, apparatus, electronic device and storage medium for edge-cloud collaborative partial discharge detection.

[0005] To achieve the above objectives, this application provides a method for partial discharge detection using edge-cloud collaboration, comprising: The first edge partial discharge detection device receives partial discharge data sensed by at least one partial discharge detection sensor, which is close to the object being detected. The first edge partial discharge detection device determines whether the partial discharge data contains a partial discharge phenomenon. When the partial discharge phenomenon is not present, the device sends the partial discharge data to the second edge partial discharge detection device and receives the feedback result from the second edge partial discharge detection device. The first edge partial discharge detection device determines that the feedback result of the second edge partial discharge detection device is that there is no partial discharge phenomenon, and sends the partial discharge data to the cloud partial discharge detection device corresponding to the first edge partial discharge detection device. The first edge partial discharge detection device acquires the feedback result from the cloud partial discharge detection device and performs partial discharge detection based on the feedback result.

[0006] Based on the same concept, this application also provides a device for edge-cloud collaborative partial discharge detection, comprising: A receiving module is used to receive partial discharge data sensed by at least one partial discharge detection sensor, wherein the partial discharge detection sensor is close to the object being detected. The first judgment and processing module judges whether the partial discharge data has a partial discharge phenomenon. When the partial discharge phenomenon does not exist, the partial discharge data is sent to the second edge partial discharge detection device and the feedback result of the second edge partial discharge detection device is received. The second judgment and processing module is used to determine that the feedback result of the second edge partial discharge detection device is that there is no partial discharge phenomenon, and to send the partial discharge data to the cloud partial discharge detection device corresponding to the first edge partial discharge detection device. The execution module is used for the edge partial discharge detection device to obtain the feedback results from the cloud partial discharge detection device and to perform partial discharge detection based on the feedback results.

[0007] Based on the same concept, this application also provides an electronic device, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the edge-cloud collaborative partial discharge detection method as described in any of the preceding claims.

[0008] Based on the same concept, this application also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the edge-cloud collaborative partial discharge detection method as described in any of the preceding claims. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments will be briefly described below. Obviously, the drawings described below only relate to some embodiments of the present invention and are not intended to limit the present invention.

[0010] Figure 1 This is a schematic flowchart of a method for partial discharge detection using edge-cloud collaboration provided in an embodiment of this application; Figure 2 This is a schematic diagram of the partial discharge detection system provided in the embodiments of this application; Figure 3 This is another schematic diagram of the edge-cloud collaborative partial discharge detection provided in an embodiment of this application; Figure 4 This is another schematic diagram of the edge-cloud collaborative partial discharge detection provided in the embodiments of this application; Figure 5 This is another schematic diagram of the edge-cloud collaborative partial discharge detection provided in the embodiments of this application; Figure 6 This is an apparatus for partial discharge detection using edge-cloud collaboration, provided according to embodiments of this application; Figure 7 This is a schematic diagram of an electronic device structure provided according to an embodiment of this application; Figure 8 This is a schematic diagram of a storage medium provided according to an embodiment of this application. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] Unless otherwise defined, the technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains. The terms “first,” “second,” and similar terms used in the specification and claims of this patent application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as “comprising” or “including” mean that the technical feature preceding the term encompasses the technical features listed following the term and their equivalents, without excluding other technical features.

[0013] At least one embodiment of this application provides a method for edge-cloud collaborative partial discharge detection. The method includes: receiving partial discharge data sensed by at least one partial discharge detection sensor, the sensor being close to a target object; determining whether a partial discharge phenomenon exists in the partial discharge data; if no partial discharge phenomenon exists, sending the partial discharge data to a second edge partial discharge detection device and receiving feedback from the second edge partial discharge detection device; determining that the feedback from the second edge partial discharge detection device indicates no partial discharge phenomenon exists, and sending the partial discharge data to a cloud-based partial discharge detection device corresponding to the first edge partial discharge detection device; obtaining feedback from the cloud-based partial discharge detection device, and performing partial discharge detection based on the feedback result. This method utilizes edge-cloud collaborative partial discharge detection, fully leveraging the advantages of both edge and cloud-based partial discharge detection to improve the efficiency of partial discharge detection.

[0014] At least one embodiment of this application also provides an edge-cloud collaborative partial discharge detection device, comprising: a receiving module for receiving partial discharge data sensed by at least one partial discharge detection sensor, the partial discharge detection sensor being close to the object being detected; a first judgment and processing module for judging whether the partial discharge data indicates the presence of a partial discharge phenomenon, and when the partial discharge phenomenon is not present, sending the partial discharge data to a second edge partial discharge detection device and receiving feedback results from the second edge partial discharge detection device; a second judgment and processing module for judging that the feedback result from the second edge partial discharge detection device indicates the absence of a partial discharge phenomenon, and sending the partial discharge data to a cloud-based partial discharge detection device corresponding to the first edge partial discharge detection device; and an execution module for the edge partial discharge detection device to obtain the feedback result from the cloud-based partial discharge detection device and perform partial discharge detection based on the feedback result. This device performs partial discharge detection through edge-cloud collaboration, fully utilizing the advantages of edge partial discharge detection and cloud-based partial discharge detection, thereby improving the efficiency of partial discharge detection.

[0015] At least one embodiment of this disclosure also provides an electronic device, which includes: one or more processors and a storage device; the storage device is used to store one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement any of the edge-cloud collaborative partial discharge detection methods provided in the embodiments of this disclosure.

[0016] At least one embodiment of this disclosure also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform any of the edge-cloud collaborative partial discharge detection methods provided in the embodiments of this disclosure.

[0017] Figure 1 This is a schematic flowchart of an edge-cloud collaborative partial discharge detection method provided in an embodiment of this application. Figure 1 As shown, the method includes: Step 102: Receive partial discharge data sensed by at least one partial discharge detection sensor, wherein the partial discharge detection sensor is close to the object being detected; According to embodiments of this disclosure, the partial discharge detection sensor includes one or more of the following: an ultra-high frequency sensor, an ultrasonic sensor, a transient ground voltage sensor, a high frequency current transformer, an optical sensor, and a chemical sensor.

[0018] Step 104: Determine whether the partial discharge data contains a partial discharge phenomenon. If the partial discharge phenomenon does not exist, send the partial discharge data to the second edge partial discharge detection device and receive the feedback result from the second edge partial discharge detection device. According to embodiments of this disclosure, receiving partial discharge data sensed by at least one partial discharge detection sensor further includes: acquiring partial discharge characteristics of the partial discharge data, the partial discharge characteristics including one or more of voltage phase, maximum discharge amplitude, average discharge amplitude, number of discharges, pulse amplitude, pulse rise time, pulse fall time, pulse width, and pulse area.

[0019] According to embodiments of this disclosure, determining whether the partial discharge data exhibits a partial discharge phenomenon includes determining whether the partial discharge characteristics exhibit a partial discharge phenomenon.

[0020] According to embodiments of this disclosure, a local network connection exists between the first edge partial discharge detection device and the second edge partial discharge detection device. The local network connection can be a wired or wireless network connection.

[0021] Step 106: Determine that the feedback result of the second edge partial discharge detection device is that there is no partial discharge phenomenon, and send the partial discharge data to the cloud partial discharge detection device corresponding to the first edge partial discharge detection device; According to embodiments of this disclosure, a remote network connection exists between the first edge partial discharge detection device and the cloud partial discharge detection device, and the local network connection can be a wired or wireless network connection.

[0022] Step 108: Obtain the feedback result from the cloud-based partial discharge detection device, and perform partial discharge detection based on the feedback result.

[0023] According to embodiments of this disclosure, the first edge partial discharge detection device, the second edge partial discharge detection device, and / or the cloud-based partial discharge device can determine whether a partial discharge phenomenon exists through a neural network model.

[0024] According to embodiments of this disclosure, the neural network model may employ one or more of the following: backpropagation neural network, KOHONEN self-organizing feature map neural network, radial basis function neural network, and cascaded neural network.

[0025] According to embodiments of this disclosure, the edge partial discharge detection device is used to detect partial discharge phenomena in the late stage of partial discharge, and the cloud partial discharge detection device is used to detect partial discharge phenomena in the early and middle stages of partial discharge. The partial discharge detection capability of the cloud partial discharge detection device is greater than that of the edge partial discharge detection device.

[0026] According to embodiments of this disclosure, the edge partial discharge detection device is used to detect partial discharge phenomena of pulsed discharge and continuous discharge, the cloud partial discharge detection device is used to detect random discharge, and the partial discharge detection capability of the cloud partial discharge detection device is greater than that of the edge partial discharge detection device.

[0027] Figure 2 This is a schematic diagram of the edge-cloud partial discharge detection system provided in an embodiment of this application. The cloud-based partial discharge detection device and the edge partial discharge detection device are connected through an edge-cloud collaborative component. The cloud-based partial discharge detection device includes a sample library and a model library. The sample library includes various partial discharge samples, and the model library includes various partial discharge models.

[0028] Edge partial discharge detection equipment includes one or more partial discharge detection models. Due to the limited processing power of edge partial discharge detection equipment, it typically does not deploy all known types of partial discharge detection models. For example... Figure 2 The left edge partial discharge detection device includes a free metal particle discharge detection module and a corona discharge detection module; the middle edge partial discharge detection device includes an insulation defect detection module and a floating potential discharge detection module; and the right edge partial discharge detection device includes a corona discharge detection module and a floating potential discharge detection module.

[0029] Edge partial discharge detection equipment acquires partial discharge signals from the object to be detected and performs partial discharge detection through a partial discharge detection module. Since different edge partial discharge detection equipment have varying partial discharge detection capabilities, they can transmit partial discharge signals through connections between different edge partial discharge detection equipment.

[0030] Cloud-based partial discharge detection equipment can send partial discharge models to edge-based partial discharge detection equipment through edge-cloud collaborative components.

[0031] Figure 3 This is another schematic flowchart illustrating the edge-cloud collaborative partial discharge detection method provided in an embodiment of this application. For example... Figure 3 As shown, the method includes: Step 302: Receive partial discharge data sensed by at least one partial discharge detection sensor, wherein the partial discharge detection sensor is close to the object being detected; Step 304: When it is determined that the partial discharge phenomenon exists, the partial discharge event corresponding to the partial discharge phenomenon is sent to the cloud-based partial discharge detection device; According to an embodiment of this disclosure, when it is determined that the partial discharge phenomenon exists, the partial discharge result is sent to the cloud-based partial discharge detection device.

[0032] According to embodiments of this disclosure, the partial discharge result includes late partial discharge, mid partial discharge, and early partial discharge.

[0033] According to embodiments of this disclosure, the partial discharge signal includes pulsed discharge, continuous discharge, and random discharge.

[0034] Step 306: When it is determined that the partial discharge phenomenon exists, the partial discharge data corresponding to the partial discharge phenomenon is sent to the cloud-based partial discharge detection device.

[0035] According to an embodiment of this disclosure, when it is determined that the partial discharge phenomenon exists, the partial discharge signal is sent to the cloud-based partial discharge detection device.

[0036] According to embodiments of this disclosure, the partial discharge signal includes one or more of the following: time-domain features (pulse amplitude, rise time, number of discharges / phase), frequency-domain features (spectrum, wavelet energy coefficient), and statistical features (skewness, kurtosis, pulse repetition rate).

[0037] According to embodiments of this disclosure, when an edge partial discharge detection device determines that a partial discharge phenomenon exists, it sends the partial discharge event to a cloud partial discharge detection device, so that the cloud partial discharge detection device can comprehensively process and analyze the partial discharge events detected by multiple edge partial discharge detection devices to obtain a more accurate partial discharge detection result.

[0038] According to an embodiment of this disclosure, when the edge partial discharge detection device determines that a partial discharge phenomenon exists, it sends the partial discharge data corresponding to the partial discharge phenomenon to the cloud partial discharge detection device so that the cloud partial discharge detection device can make a secondary judgment. If the result of the secondary judgment is the same as the judgment result of the edge partial discharge detection, it can be determined that a partial discharge phenomenon exists. If the judgment results are different, the judgment result of the cloud edge detection device shall prevail.

[0039] According to embodiments of this disclosure, if the result of the secondary judgment is different from the judgment result of the edge partial discharge detection, the cloud-based partial discharge detection device can control other edge partial discharge detection devices to acquire partial discharge data and perform collaborative detection of partial discharge.

[0040] Figure 4 This is another schematic flowchart of the edge-cloud collaborative partial discharge detection method provided in the embodiments of this application. Figure 4 As shown, the method includes: Step 402: Receive partial discharge data sensed by at least one partial discharge detection sensor, wherein the partial discharge detection sensor is close to the object being detected; Step 404: Determine whether the partial discharge data contains a partial discharge phenomenon. If the partial discharge phenomenon does not exist, send the partial discharge data to the second edge partial discharge detection device and receive the feedback result from the second edge partial discharge detection device. According to an embodiment of this disclosure, if it is determined that the partial discharge signal does not exhibit partial discharge phenomena, the partial discharge signal is sent to a second edge partial discharge detection device.

[0041] According to embodiments of this disclosure, the partial discharge signal includes one or more of the following: time-domain features (pulse amplitude, rise time, number of discharges / phase), frequency-domain features (spectrum, wavelet energy coefficient), and statistical features (skewness, kurtosis, pulse repetition rate).

[0042] Step 406: Determine that the feedback result of the second edge partial discharge detection device is that a partial discharge phenomenon exists, and send the partial discharge data corresponding to the partial discharge phenomenon to the second edge partial discharge detection device.

[0043] According to an embodiment of this disclosure, if the feedback result of the second edge partial discharge detection device is determined to indicate the presence of a partial discharge phenomenon, the partial discharge signal corresponding to the partial discharge phenomenon is sent to the second edge partial discharge detection device.

[0044] According to embodiments of this disclosure, the partial discharge signal includes one or more of the following: time-domain features (pulse amplitude, rise time, number of discharges / phase), frequency-domain features (spectrum, wavelet energy coefficient), and statistical features (skewness, kurtosis, pulse repetition rate).

[0045] According to embodiments of this disclosure, when a first edge partial discharge detection device determines that no partial discharge phenomenon exists, it sends the partial discharge data to a second edge partial discharge detection device and receives feedback results from the second edge partial discharge detection device. The partial discharge detection capabilities of the second and first edge partial discharge detection devices may be the same or different. If the capabilities are the same, the second edge partial discharge detection device performs a second detection. If the capabilities are different, the detection capability of the second edge partial discharge detection device may be greater than that of the first edge partial discharge detection device. In this case, the reliability of the partial discharge detection results from the second edge partial discharge detection device is greater than the reliability of the partial discharge detection results from the first edge partial discharge detection device, thus improving the overall reliability of the partial discharge detection results.

[0046] According to an embodiment of this disclosure, the feedback result of the second edge partial discharge detection device is that a partial discharge phenomenon exists. The second edge partial discharge detection device is the priority processing device for the partial discharge data. The first edge partial discharge detection device sends the partial discharge data corresponding to the partial discharge phenomenon to the second edge partial discharge detection device. Through the above data flow, the invalid work of the first edge partial discharge detection device is avoided, and the efficiency of partial discharge detection is improved.

[0047] Figure 5 This is another schematic flowchart of the edge-cloud collaborative partial discharge detection method provided in the embodiments of this application. Figure 5 As shown, the method includes: Step 502: Receive partial discharge data sensed by at least one partial discharge detection sensor, wherein the partial discharge detection sensor is close to the object being detected; Step 504: Determine whether the partial discharge data contains a partial discharge phenomenon. If the partial discharge phenomenon does not exist, send the partial discharge data to the second edge partial discharge detection device and receive the feedback result from the second edge partial discharge detection device. Step 506: Determine that the feedback result of the second edge partial discharge detection device is that there is no partial discharge phenomenon, and send the partial discharge data to the cloud partial discharge detection device corresponding to the first edge partial discharge detection device; Step 508: If the feedback result from the cloud-based partial discharge detection device indicates that there is no partial discharge phenomenon, control the edge partial discharge detection device to stop acquiring partial discharge data sensed by the partial discharge detection sensor; or if the feedback result from the cloud-based partial discharge detection device indicates that there is no partial discharge phenomenon, control the edge partial discharge detection device to reduce the frequency of acquiring partial discharge data sensed by the partial discharge detection sensor.

[0048] According to embodiments of this disclosure, if the feedback result from the second edge partial discharge detection device indicates that no partial discharge phenomenon exists, the partial discharge data is sent to the cloud-based partial discharge detection device corresponding to the first edge partial discharge detection device. Since the detection capability of the cloud-based partial discharge detection device is greater than that of the edge partial discharge detection device, the participation of the cloud-based partial discharge detection device is necessary for high-risk partial discharge types to detect potential partial discharge risks in advance and improve the efficiency of partial discharge detection.

[0049] Figure 6 This is an edge-cloud collaborative partial discharge detection device provided according to embodiments of this application, such as... Figure 6 As shown, the edge-cloud collaborative partial discharge detection device 500 includes: The receiving module 610 is used to receive partial discharge data sensed by at least one partial discharge detection sensor, wherein the partial discharge detection sensor is close to the object being detected. The first judgment and processing module 620 is used to judge whether the partial discharge data has a partial discharge phenomenon. When the partial discharge phenomenon does not exist, the partial discharge data is sent to the second edge partial discharge detection device and the feedback result of the second edge partial discharge detection device is received. The second judgment and processing module 630 is used to judge that the feedback result of the second edge partial discharge detection device is that there is no partial discharge phenomenon, and send the partial discharge data to the cloud partial discharge detection device corresponding to the first edge partial discharge detection device. The execution module 640 is used to obtain the feedback results of the cloud-based partial discharge detection device and perform partial discharge detection based on the feedback results.

[0050] The device system provided in this disclosure can achieve the same working process and technical effect as the embodiment of the ultra-fast transient overvoltage automatic detection method, which will not be repeated here. Please refer to the previous description.

[0051] At least one embodiment of this disclosure also provides an electronic device 700, see reference. Figure 7 The electronic device 700 includes one or more processors 710 and a memory 720; the memory 720 is used to store one or more programs, which, when executed by one or more processors, enable the one or more processors to implement any of the edge-cloud collaborative partial discharge detection methods provided in the embodiments of this disclosure.

[0052] At least one embodiment of this application also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform any of the edge-cloud collaborative partial discharge detection methods provided in the embodiments of this disclosure.

[0053] The storage medium for the computer-executable instructions provided in at least one embodiment of this disclosure may be a non-transitory computer-readable storage medium. Exemplarily, Figure 8 This is a schematic diagram of a non-transitory computer-readable storage medium provided for at least one embodiment of the present disclosure.

[0054] For example, such as Figure 8 As shown, computer-readable instructions 801 are non-transitory stored on computer-readable storage medium 800. For example, when computer-readable instructions 801 are executed by a processor, one or more steps in the ultrafast transient overvoltage automatic detection method described above can be performed.

[0055] For example, the storage medium 800 can be used in the electronic device 700 described above. For example, the storage medium 800 may include the memory 720 in the electronic device 700.

[0056] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0057] The following points need to be explained: (1) The accompanying drawings of the embodiments of this disclosure only involve the structures involved in the embodiments of this disclosure. Other structures can be referred to the general design.

[0058] (2) Where there is no conflict, the embodiments of this disclosure and the features in the embodiments can be combined with each other to obtain new embodiments.

[0059] The above description is merely an exemplary embodiment of the present invention and is not intended to limit the scope of protection of the present invention, which is determined by the appended claims.

Claims

1. A method for partial discharge detection using edge-cloud collaboration, characterized in that, include: The first edge partial discharge detection device receives partial discharge data sensed by at least one partial discharge detection sensor, which is close to the object being detected. The first edge partial discharge detection device determines whether the partial discharge data contains a partial discharge phenomenon. When the partial discharge phenomenon is not present, it sends an edge partial discharge detection request to the second edge partial discharge detection device associated with the first edge partial discharge detection device. The edge partial discharge detection request includes the partial discharge data and the first partial discharge detection model identifier of the first edge partial discharge detection device. The first edge partial discharge detection device acquires and judges the feedback result of the second edge partial discharge detection device. When the feedback result of the second edge partial discharge detection device is that there is no partial discharge phenomenon, it sends a cloud partial discharge detection request to the cloud partial discharge detection device associated with the first edge partial discharge detection device. The cloud partial discharge detection request includes the partial discharge data, the first partial discharge detection model identifier, and the second partial discharge detection model identifier of the second edge partial discharge detection device. The first edge partial discharge detection device acquires the feedback result from the cloud partial discharge detection device and performs partial discharge detection based on the feedback result from the cloud partial discharge detection device.

2. The method according to claim 1, characterized in that, The first edge partial discharge detection device determines that there is a partial discharge phenomenon in the partial discharge detection data, and then the method further includes: the first edge partial discharge detection device sends the partial discharge event corresponding to the partial discharge phenomenon to the cloud partial discharge detection device associated with the first edge partial discharge detection device.

3. The method according to claim 2, characterized in that, When the first edge partial discharge detection device acquires and determines that the feedback result from the second edge partial discharge detection device indicates the presence of partial discharge, the process then includes: The first edge partial discharge detection device acquires the second partial discharge data and sends the second partial discharge data to the second edge partial discharge detection device.

4. The method according to claim 3, characterized in that, The first edge partial discharge detection device acquires the second partial discharge detection model identifier of the second edge partial discharge detection device and sends the second partial discharge detection model identifier to the cloud partial discharge detection device, so that the cloud partial discharge detection device can acquire the second partial discharge detection model through the second partial discharge detection model identifier.

5. The method according to claim 1, characterized in that, The first edge partial discharge detection device acquires the feedback result from the cloud partial discharge detection device and performs partial discharge detection based on the feedback result from the cloud partial discharge detection device, including: If the feedback result from the cloud-based partial discharge detection device indicates the presence of partial discharge, the first edge partial discharge detection device is controlled to acquire the partial discharge data sensed by the at least one partial discharge detection sensor and report it to the cloud-based partial discharge detection device.

6. The method according to claim 1, characterized in that, The first edge partial discharge detection device acquires the feedback result of the cloud partial discharge detection device and performs partial discharge detection based on the feedback result of the cloud partial discharge detection device, further comprising: The first edge partial discharge detection device acquires the edge partial discharge detection model of the cloud partial discharge detection device and sends the edge partial discharge detection model to the second edge partial discharge detection device.

7. The method according to claim 1, characterized in that, The step of obtaining the feedback result from the cloud-based partial discharge detection device and performing partial discharge detection based on the feedback result includes: If the cloud-based partial discharge detection device receives a feedback result indicating that no partial discharge phenomenon exists, the first edge partial discharge detection device is controlled to stop acquiring partial discharge data sensed by the partial discharge detection sensor, or... If the feedback result from the cloud-based partial discharge detection device indicates that there is no partial discharge phenomenon, the first edge partial discharge detection device is controlled to reduce the frequency of acquiring partial discharge data sensed by the partial discharge detection sensor.

8. A device for edge-cloud collaborative partial discharge detection, comprising a first edge partial discharge detection device, characterized in that, The first edge partial discharge detection device includes: A receiving module is used to receive partial discharge data sensed by at least one partial discharge detection sensor, which is close to the object being detected. The first judgment and processing module is used to determine whether the partial discharge data has a partial discharge phenomenon. When the partial discharge phenomenon is not present, it sends an edge partial discharge detection request to the second edge partial discharge detection device associated with the first edge partial discharge detection device. The edge partial discharge detection request includes the partial discharge data and the first partial discharge detection model identifier of the first edge partial discharge detection device. The second judgment and processing module is used to obtain and judge the feedback result of the second edge partial discharge detection device. When the feedback result of the second edge partial discharge detection device is that there is no partial discharge phenomenon, it sends a cloud partial discharge detection request to the cloud partial discharge detection device associated with the first edge partial discharge detection device. The cloud partial discharge detection request includes the partial discharge data, the first partial discharge detection model identifier, and the second partial discharge detection model identifier of the second edge partial discharge detection device. The execution module is used to obtain the feedback results of the cloud-based partial discharge detection device and perform partial discharge detection based on the feedback results of the cloud-based partial discharge detection device.

9. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the edge-cloud collaborative partial discharge detection method as described in any one of claims 1-7.

10. A storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the edge-cloud collaborative partial discharge detection method as described in any one of claims 1-7.

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