Remote monitoring method, device, equipment and storage medium for power distribution switch cabinet

Abstract

The present invention relates to the technical field of smart power plants, and in particular to a remote monitoring method, device, equipment and storage medium for a distribution switch cabinet. The present invention collects a local discharge digital data stream of a distribution switch cabinet; generates a discharge phase distribution spectrum based on the local discharge digital data stream; performs spectrum recognition based on the discharge phase distribution spectrum through a trained local discharge defect detection model to obtain a spectrum feature probability set; outputs a remote detection report of the distribution switch cabinet according to the spectrum feature probability set, constructs a discharge phase distribution spectrum of the switch cabinet through the local discharge digital data stream of the distribution switch cabinet, and then detects the discharge phase distribution spectrum through the trained local discharge defect detection model to determine the local discharge state of the distribution switch cabinet, thereby achieving the purpose of remotely detecting the operating state of the switch cabinet.

Description

Technical Field

[0001] The present invention relates to the technical field of smart power plants, and in particular to a remote monitoring method, device, equipment and storage medium for a distribution switch cabinet. Background Art

[0002] Switchgear is an important equipment in the power distribution network. Detecting the operating status of the switchgear is very important for maintaining the normal operation of the distribution network. The traditional monitoring method of the distribution switchgear is mainly through detecting the transient potential of the switchgear. If the transient potential is higher than a certain threshold, it means that the switchgear has a discharge defect. However, this judgment method is extremely limited. In the face of different types of partial discharges, it cannot truly reflect the actual discharge status of the distribution switchgear, and the monitoring effect is poor.

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

[0004] The main purpose of the present invention is to provide a remote monitoring method, device, equipment and storage medium for a distribution switch cabinet, aiming to solve the technical problem of poor partial discharge monitoring effect of a distribution switch cabinet in the prior art.

[0005] To achieve the above object, the present invention provides a remote monitoring method for a power distribution switch cabinet, the method comprising the following steps:

[0006] Collect partial discharge digital data streams from distribution switchgear;

[0007] Generate a discharge phase distribution map based on the partial discharge digital data stream;

[0008] Based on the discharge phase distribution spectrum, spectrum recognition is performed through a trained partial discharge defect detection model to obtain a spectrum feature probability set;

[0009] A remote detection report of the power distribution switch cabinet is output according to the graph feature probability set.

[0010] Optionally, the performing spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set includes:

[0011] Extracting features from the discharge phase distribution spectrum to obtain pulse amplitude variation, discharge amplitude variation trend, discharge times and discharge time interval;

[0012] Determine the discharge type of the discharge phase distribution spectrum according to at least one of the pulse amplitude change amount, the discharge amplitude change trend, the number of discharges and the discharge time interval;

[0013] A spectral feature probability set is generated according to the discharge type.

[0014] Optionally, determining the discharge type of the discharge phase distribution spectrum according to at least one of the pulse amplitude change amount, the discharge amplitude change trend, the number of discharges and the discharge time interval includes:

[0015] Statistically determining a distribution range of the discharge signal according to the discharge time interval;

[0016] When the distribution range is concentrated, and the pulse amplitude variation is greater than the target pulse peak threshold, determining that the discharge type of the discharge phase distribution spectrum is a spike discharge;

[0017] or

[0018] When the discharge time intervals of adjacent discharge signals are equal and the number of discharges is negatively correlated with the phase of the discharge phase distribution spectrum, determining that the discharge type of the discharge phase distribution spectrum is suspended discharge;

[0019] or

[0020] When the distribution range is concentrated and the discharge amplitude variation trend of each discharge signal is uniformly distributed, it is determined that the discharge type of the discharge phase distribution spectrum is air gap discharge.

[0021] Optionally, collecting the partial discharge digital data stream of the power distribution switch cabinet includes:

[0022] Collect partial discharge simulation signals from distribution switch cabinets;

[0023] Performing denoising processing on the partial discharge simulation signal to obtain a target partial discharge simulation signal;

[0024] The target partial discharge signal is converted into a partial discharge digital data stream.

[0025] Optionally, the performing denoising processing on the partial discharge simulation signal to obtain a target partial discharge simulation signal includes:

[0026] Performing wavelet decomposition of multiple scales on the partial discharge simulation signal to obtain wavelet coefficients of multiple scales;

[0027] Perform coefficient denoising on the wavelet coefficients of the multiple scales based on a preset analysis threshold to obtain target wavelet coefficients;

[0028] The target partial discharge simulation signal is obtained by performing inverse wavelet transform reconstruction based on the target wavelet coefficients.

[0029] Optionally, converting the target partial discharge signal into a partial discharge digital data stream comprises:

[0030] extracting the pulse frequency of the target partial discharge signal;

[0031] Determine the capture bandwidth of the analog-to-digital conversion device according to the pulse frequency and the preset magnification;

[0032] The target partial discharge signal is converted into a partial discharge digital data stream by the analog-to-digital conversion device based on the capture bandwidth.

[0033] In addition, to achieve the above-mentioned purpose, the present invention further proposes a remote monitoring device for a power distribution switch cabinet, the remote monitoring device for a power distribution switch cabinet comprising:

[0034] A collection module is used to collect the partial discharge digital data stream of the distribution switch cabinet;

[0035] A generating module, used for generating a discharge phase distribution spectrum based on the partial discharge digital data stream;

[0036] An identification module, used for performing spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set;

[0037] An output module is used to output a remote detection report of the distribution switch cabinet according to the graph feature probability set.

[0038] In addition, to achieve the above-mentioned purpose, the present invention also proposes a remote monitoring device for a distribution switch cabinet, the remote monitoring device for the distribution switch cabinet comprising: a memory, a processor, and a remote monitoring program for the distribution switch cabinet stored in the memory and executable on the processor, the remote monitoring program for the distribution switch cabinet being configured to implement the steps of the remote monitoring method for the distribution switch cabinet as described above.

[0039] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a remote monitoring program for a distribution switch cabinet is stored. When the remote monitoring program for the distribution switch cabinet is executed by a processor, the steps of the remote monitoring method for the distribution switch cabinet as described above are implemented.

[0040] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the remote monitoring method of the distribution switch cabinet as described above.

[0041] One or more technical solutions proposed in the present invention have at least the following technical effects: the present invention collects the local discharge digital data stream of the distribution switch cabinet; generates a discharge phase distribution spectrum based on the local discharge digital data stream; performs spectrum recognition through a trained local discharge defect detection model based on the discharge phase distribution spectrum to obtain a spectrum feature probability set; outputs a remote detection report of the distribution switch cabinet according to the spectrum feature probability set, constructs a discharge phase distribution spectrum of the switch cabinet through the local discharge digital data stream of the distribution switch cabinet, and then detects the discharge phase distribution spectrum through the trained local discharge defect detection model to determine the local discharge state of the distribution switch cabinet, thereby achieving the purpose of remotely detecting the operating state of the switch cabinet and avoiding the technical problem of poor effect of monitoring the local discharge of the distribution switch cabinet in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 It is a flow chart of a first embodiment of a remote monitoring method for a power distribution switch cabinet of the present invention;

[0045] Figure 2 It is a flow chart of a second embodiment of a remote monitoring method for a power distribution switch cabinet of the present invention;

[0046] Figure 3 It is a flow chart of a third embodiment of a remote monitoring method for a power distribution switch cabinet of the present invention;

[0047] Figure 4 It is a structural block diagram of a first embodiment of a remote monitoring device for a power distribution switch cabinet of the present invention;

[0048] Figure 5 It is a structural schematic diagram of a remote monitoring device for a power distribution switch cabinet in a hardware operating environment involved in an embodiment of the present invention.

[0049] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0050] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0051] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0052] Based on this, an embodiment of the present invention provides a remote monitoring method for a power distribution switch cabinet, referring to Figure 1 , Figure 1 The figure is a flow chart of a first embodiment of a remote monitoring method for a power distribution switch cabinet according to the present invention.

[0053] In this embodiment, the remote monitoring method of the power distribution switch cabinet includes:

[0054] Step S10: collecting the partial discharge digital data stream of the distribution switch cabinet.

[0055] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a control computer, etc. The following takes the control computer as an example to illustrate this embodiment and the following embodiments.

[0056] It should be noted that as the distribution switch cabinet grows in service life, it will face risks such as insulation degradation or loose components, which will lead to partial discharge when high-voltage charge flows in, further damaging components or posing a threat to the personal safety of workers. In addition, the maintenance methods corresponding to different types of partial discharges are also different. In order to increase the service life of the switch cabinet and reduce maintenance costs, it is necessary to monitor and record the partial discharge status of the distribution switch cabinet.

[0057] It can be understood that the partial discharge digital data stream refers to the partial discharge digital signal that can be directly recognized by the control computer. In the present embodiment, since the discharge of the switch cabinet is an external discharge between components and components, and between devices, only analog data of the partial discharge can be collected when collecting data. Therefore, in the present embodiment, it is also necessary to perform analog-to-digital conversion on the collected initial data to obtain a partial discharge array data stream that can be recognized by the computer.

[0058] Step S20: generating a discharge phase distribution map based on the partial discharge digital data stream.

[0059] It should be noted that the partial discharge digital data stream is a characteristic parameter that can be repeatedly detected during the operation of the equipment and will not be affected by the external environment. Therefore, the discharge phase distribution map constructed based on the partial discharge digital data stream can characterize the operating status of the switchgear. Since different types of partial discharges correspond to differences in discharge distribution, discharge frequency, discharge amplitude and other parameters, the difference is more obvious when constructing a visual discharge phase distribution map, which improves the defect identification efficiency of subsequent switchgear.

[0060] In a specific implementation, the discharge phase distribution spectrum includes a discharge number-cycle phase spectrum, a discharge amount-cycle phase spectrum, and a spatial three-dimensional spectrum, wherein the characterization formula of the discharge number-cycle phase spectrum is:

[0061]

[0062] Wherein, M represents the number of power frequency cycles, and nk represents the number of discharges in the kth cycle.

[0063] The characterization formula of the discharge amount-cycle phase spectrum is:

[0064]

[0065] Wherein, M represents the number of power frequency cycles, and qki represents the discharge amount of the i-th discharge in the k-th cycle.

[0066] The spatial three-dimensional map reflects the mapping relationship between the discharge amount, cycle phase and discharge number. The characterization formula of the spatial three-dimensional map is:

[0067]

[0068] in, It represents the number of discharges counted by the grid under the kth power frequency cycle, and N represents the number of power frequency cycles collected.

[0069] Step S30: performing spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set.

[0070] It should be understood that the trained partial discharge defect detection model can extract the features of the visualized discharge phase distribution map, explore the pulse amplitude change, discharge amplitude change trend, discharge number and discharge time interval from a higher dimensional perspective, and thus identify the discharge type corresponding to the discharge phase distribution map.

[0071] In a specific implementation, since more than a single part of local discharge may occur in the switch cabinet, during detection, the characteristics of the collected data may be interfered by the external environment when being processed, thereby affecting the accuracy of the spectrum. Therefore, during the process of spectrum recognition, this embodiment outputs a spectrum feature probability set, which records the probability of which type of local discharge the discharge phase distribution spectrum is.

[0072] Step S40: outputting a remote detection report of the power distribution switch cabinet according to the graph feature probability set.

[0073] It is understandable that the remote detection report is used to provide maintenance assistance information to the staff, thereby improving maintenance efficiency and reducing losses caused by equipment damage.

[0074] This embodiment collects the partial discharge digital data stream of the distribution switch cabinet; generates a discharge phase distribution spectrum based on the partial discharge digital data stream; performs spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set; outputs a remote detection report of the distribution switch cabinet according to the spectrum feature probability set, constructs a discharge phase distribution spectrum of the switch cabinet through the partial discharge digital data stream of the distribution switch cabinet, and then detects the discharge phase distribution spectrum through the trained partial discharge defect detection model to determine the partial discharge state of the distribution switch cabinet, thereby achieving the purpose of remotely detecting the operating state of the switch cabinet and avoiding the technical problem of poor effect of monitoring partial discharge of the distribution switch cabinet in the prior art.

[0075] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S30, comprising:

[0076] Step S301: extracting features from the discharge phase distribution spectrum to obtain pulse amplitude variation, discharge amplitude variation trend, discharge times and discharge time interval.

[0077] Step S302: Determine the discharge type of the discharge phase distribution spectrum according to at least one of the pulse amplitude change, the discharge amplitude change trend, the number of discharges, and the discharge time interval.

[0078] Step S303: generating a spectrum feature probability set according to the discharge type.

[0079] It should be noted that feature extraction of the discharge phase distribution spectrum can be performed by extracting discharge characteristic parameters in the discharge phase distribution spectrum using principal component analysis algorithm, linear discriminant analysis, etc., to obtain pulse amplitude change, discharge amplitude change trend, discharge number and discharge time interval.

[0080] Among them, the change in pulse amplitude refers to the change in pulse amplitude compared with the normal operation of the switchgear; the discharge amplitude change trend refers to the month-on-month change in discharge distribution in each period in the time domain when local discharge exists; the number of discharges refers to the total number of discharges in the current cycle; and the discharge time interval refers to the interval between two adjacent discharges.

[0081] Further, the determining the discharge type of the discharge phase distribution spectrum according to at least one of the pulse amplitude change trend, the discharge amplitude change trend, the number of discharges and the discharge time interval includes:

[0082] Statistically determining a distribution range of the discharge signal according to the discharge time interval;

[0083] When the distribution range is concentrated, and the pulse amplitude variation is greater than the target pulse peak threshold, determining that the discharge type of the discharge phase distribution spectrum is a spike discharge;

[0084] or

[0085] When the discharge time intervals of adjacent discharge signals are equal and the number of discharges is negatively correlated with the phase of the discharge phase distribution spectrum, determining that the discharge type of the discharge phase distribution spectrum is suspended discharge;

[0086] or

[0087] When the distribution range is concentrated and the discharge amplitude variation trend of each discharge signal is uniformly distributed, it is determined that the discharge type of the discharge phase distribution spectrum is air gap discharge.

[0088] In a specific implementation, spike discharge is a discharge that occurs when the electric field strength on the surface of the conductor reaches the breakdown field strength of the gas under the condition of extremely uneven electrodes. The charge density of the conductor is related to the curvature of the conductor shape, so spike discharge often occurs at the tip part. Therefore, when local discharge occurs in the switch cabinet in this embodiment, the positive charge will hit the cathode, and the negative electrode will easily emit electrons.

[0089] In the discharge phase distribution spectrum, the discharge phase of spike discharge is more dispersed and asymmetric due to the polarity effect, so the pulse amplitude is larger and the discharge signal is mainly concentrated.

[0090] The initial field strength of suspended discharge is relatively large, and discharge is not easy to occur. When the required breakdown field strength is reached, there will be a discharge signal, and the number of discharges decreases with the increase of the phase. Suspended discharge mainly occurs due to the discharge phenomenon near the suspended potential body caused by the distortion of the electric field distribution between the electrode and the conductor or between the shells. Therefore, the phase characteristics and amplitude of the discharge defect are relatively stable, and the time intervals between adjacent discharges are basically the same.

[0091] The phase characteristics of air-gap discharge are relatively stable, and the discharge amplitude is widely dispersed.

[0092] This embodiment extracts features from the discharge phase distribution spectrum to obtain pulse amplitude variation trends, discharge amplitude variation trends, discharge times and discharge time intervals; determines the discharge type of the discharge phase distribution spectrum based on at least one of the pulse amplitude variation trends, discharge amplitude variation trends, discharge times and discharge time intervals; and generates a spectrum feature probability set based on the discharge type.

[0093] Based on the second embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. Figure 3 , step S10, comprising:

[0094] Step S101: collecting a partial discharge simulation signal of a power distribution switch cabinet.

[0095] Step S102: performing denoising processing on the partial discharge simulation signal to obtain a target partial discharge simulation signal.

[0096] Step S103: converting the target partial discharge signal into a partial discharge digital data stream.

[0097] It should be noted that since the discharge of the switch cabinet is an external discharge between components and between devices, when collecting data, only the analog signal of partial discharge can be collected. Therefore, in this embodiment, it is also necessary to perform analog-to-digital conversion on the collected analog signal to obtain a partial discharge array data stream that can be recognized by the computer.

[0098] In a specific implementation, since the analog signal of partial discharge is easily affected by the environmental noise during the normal operation of the switch cabinet, in order to improve the accuracy of subsequent identification of partial discharge types, this embodiment may perform denoising on the analog signal of partial discharge in advance.

[0099] Furthermore, the denoising process is performed on the partial discharge simulation signal to obtain a target partial discharge simulation signal, including:

[0100] Performing wavelet decomposition of multiple scales on the partial discharge simulation signal to obtain wavelet coefficients of multiple scales;

[0101] Perform coefficient denoising on the wavelet coefficients of the multiple scales based on a preset analysis threshold to obtain target wavelet coefficients;

[0102] The target partial discharge simulation signal is obtained by performing inverse wavelet transform reconstruction based on the target wavelet coefficients.

[0103] It is understandable that the wavelet coefficients of the environmental noise will decrease as the decomposition scale increases, because the preset analysis threshold can be associated with the scale of the wavelet decomposition, that is, the larger the decomposition scale, the smaller the preset analysis threshold.

[0104] Furthermore, converting the target partial discharge signal into a partial discharge digital data stream comprises:

[0105] extracting the pulse frequency of the target partial discharge signal;

[0106] Determine the capture bandwidth of the analog-to-digital conversion device according to the pulse frequency and the preset magnification;

[0107] The target partial discharge signal is converted into a partial discharge digital data stream by the analog-to-digital conversion device based on the capture bandwidth.

[0108] It should be noted that the preset magnification is generally greater than or equal to 2, because the partial discharge output is a pulse signal, and the transient time of the pulse signal is short. In order to accurately capture the pulse signal, it is necessary to ensure that the bandwidth of the analog-to-digital conversion device is high enough, at least greater than the pulse frequency of the pulse signal. Therefore, this embodiment sets the capture bandwidth to 2 times or more of the pulse frequency, thereby improving the accuracy of capturing the pulse signal and improving the accuracy of subsequent partial discharge identification.

[0109] This embodiment collects partial discharge analog signals from the distribution switch cabinet; performs denoising on the partial discharge analog signals to obtain target partial discharge analog signals; converts the target partial discharge signals into partial discharge digital data streams, reduces the impact of environmental noise through denoising and analog-to-digital conversion, and enables a computer to identify partial discharge signals, and performs graph recognition through a partial discharge defect detection model to determine the type of partial discharge in the switch cabinet.

[0110] This application also provides a remote monitoring device for a power distribution switch cabinet, please refer to Figure 4 , the remote monitoring device of the distribution switch cabinet comprises:

[0111] The acquisition module 10 is used to acquire the partial discharge digital data stream of the distribution switch cabinet.

[0112] The generating module 20 is used to generate a discharge phase distribution spectrum based on the partial discharge digital data stream.

[0113] The recognition module 30 is used to perform spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set.

[0114] The output module 40 is used to output a remote detection report of the distribution switch cabinet according to the graph feature probability set.

[0115] In one embodiment, the identification module 30 is also used to extract features from the discharge phase distribution spectrum to obtain pulse amplitude change trends, discharge amplitude change trends, discharge times and discharge time intervals; determine the discharge type of the discharge phase distribution spectrum based on at least one of the pulse amplitude change trends, discharge amplitude change trends, discharge times and discharge time intervals; and generate a spectrum feature probability set based on the discharge type.

[0116] In one embodiment, the identification module 30 is also used to statistically determine the distribution range of the discharge signal based on the discharge time interval; when the distribution range is concentrated, according to the pulse amplitude change amount being greater than the target pulse peak threshold, the discharge type of the discharge phase distribution map is determined to be a spike discharge; or when the discharge time intervals of adjacent discharge signals are equal and the number of discharges is negatively correlated with the phase of the discharge phase distribution map, the discharge type of the discharge phase distribution map is determined to be a suspended discharge; or when the distribution range is concentrated and the discharge amplitude change trend of each discharge signal is uniformly distributed, the discharge type of the discharge phase distribution map is determined to be an air gap discharge.

[0117] In one embodiment, the acquisition module 10 is further used to acquire a partial discharge analog signal of a distribution switch cabinet; perform denoising on the partial discharge analog signal to obtain a target partial discharge analog signal; and convert the target partial discharge signal into a partial discharge digital data stream.

[0118] In one embodiment, the acquisition module 10 is further used to perform wavelet decomposition of multiple scales on the partial discharge simulation signal to obtain wavelet coefficients of multiple scales; perform coefficient denoising on the wavelet coefficients of multiple scales based on a preset analysis threshold to obtain target wavelet coefficients; and perform inverse wavelet transform reconstruction based on the target wavelet coefficients to obtain a target partial discharge simulation signal.

[0119] In one embodiment, the acquisition module 10 is further used to extract the pulse frequency of the target partial discharge signal; determine the capture bandwidth of the analog-to-digital conversion device according to the pulse frequency and a preset magnification; and convert the target partial discharge signal into a partial discharge digital data stream through the analog-to-digital conversion device based on the capture bandwidth.

[0120] This embodiment collects the partial discharge digital data stream of the distribution switch cabinet; generates a discharge phase distribution spectrum based on the partial discharge digital data stream; performs spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set; outputs a remote detection report of the distribution switch cabinet according to the spectrum feature probability set, constructs a discharge phase distribution spectrum of the switch cabinet through the partial discharge digital data stream of the distribution switch cabinet, and then detects the discharge phase distribution spectrum through the trained partial discharge defect detection model to determine the partial discharge state of the distribution switch cabinet, thereby achieving the purpose of remotely detecting the operating state of the switch cabinet and avoiding the technical problem of poor effect of monitoring partial discharge of the distribution switch cabinet in the prior art.

[0121] The present application provides a remote monitoring device for a distribution switch cabinet, and the remote monitoring device for the distribution switch cabinet includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the remote monitoring method for the distribution switch cabinet in the above-mentioned embodiment one.

[0122] Reference below Figure 5 , which shows a schematic diagram of the structure of a remote monitoring device for a power distribution switch cabinet suitable for implementing an embodiment of the present application. The remote monitoring device for a power distribution switch cabinet in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The remote monitoring device of the power distribution switch cabinet shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0123] like Figure 5As shown, the remote monitoring device of the power distribution switch cabinet may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. Various programs and data required for the operation of the remote monitoring device of the power distribution switch cabinet are also stored in RAM1004. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the remote monitoring device of the distribution switch cabinet to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a remote monitoring device of the distribution switch cabinet with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0124] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0125] The remote monitoring device for the power distribution switch cabinet provided in the present application adopts the remote monitoring method for the power distribution switch cabinet in the above-mentioned embodiment, which can solve the technical problem of remote monitoring of the power distribution switch cabinet. Compared with the prior art, the beneficial effects of the remote monitoring device for the power distribution switch cabinet provided in the present application are the same as the beneficial effects of the remote monitoring method for the power distribution switch cabinet provided in the above-mentioned embodiment, and the other technical features in the remote monitoring device for the power distribution switch cabinet are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0126] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0127] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0128] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the remote monitoring method for the distribution switch cabinet in the above-mentioned embodiment.

[0129] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0130] The above-mentioned computer-readable storage medium may be included in the remote monitoring device of the distribution switch cabinet; or it may exist independently without being assembled into the remote monitoring device of the distribution switch cabinet.

[0131] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the remote monitoring device of the distribution switch cabinet, the remote monitoring device of the distribution switch cabinet performs remote monitoring of the distribution switch cabinet.

[0132] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0133] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0134] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0135] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned remote monitoring method for the power distribution switch cabinet, and can solve the technical problem of remote monitoring of the power distribution switch cabinet. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the remote monitoring method for the power distribution switch cabinet provided in the above-mentioned embodiment, and will not be repeated here.

[0136] The present application also provides a computer program product, including a computer program, which implements the steps of the remote monitoring method of the distribution switch cabinet as described above when the computer program is executed by a processor.

[0137] The computer program product provided in this application can solve the technical problem of remote monitoring of power distribution switch cabinets. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the remote monitoring method of power distribution switch cabinets provided in the above embodiments, which will not be repeated here.

[0138] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A remote monitoring method for a power distribution switch cabinet, characterized in that: The remote monitoring method of the power distribution switch cabinet comprises: Collect partial discharge digital data streams from distribution switchgear; Generate a discharge phase distribution map based on the partial discharge digital data stream; Based on the discharge phase distribution spectrum, spectrum recognition is performed through a trained partial discharge defect detection model to obtain a spectrum feature probability set; A remote detection report of the power distribution switch cabinet is output according to the graph feature probability set.

2. The method according to claim 1, characterized in that The method of performing spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set includes: Extracting features from the discharge phase distribution spectrum to obtain pulse amplitude variation, discharge amplitude variation trend, discharge times and discharge time interval; Determine the discharge type of the discharge phase distribution spectrum according to at least one of the pulse amplitude change amount, the discharge amplitude change trend, the number of discharges and the discharge time interval; A spectral feature probability set is generated according to the discharge type.

3. The method according to claim 2, characterized in that The step of determining the discharge type of the discharge phase distribution spectrum according to at least one of the pulse amplitude change amount, the discharge amplitude change trend, the number of discharges, and the discharge time interval comprises: Statistically determining a distribution range of the discharge signal according to the discharge time interval; When the distribution range is concentrated, and the pulse amplitude variation is greater than the target pulse peak threshold, determining that the discharge type of the discharge phase distribution spectrum is a spike discharge; or When the discharge time intervals of adjacent discharge signals are equal and the number of discharges is negatively correlated with the phase of the discharge phase distribution spectrum, determining that the discharge type of the discharge phase distribution spectrum is suspended discharge; or When the distribution range is concentrated and the discharge amplitude variation trend of each discharge signal is uniformly distributed, it is determined that the discharge type of the discharge phase distribution spectrum is air gap discharge.

4. The method according to claim 1, characterized in that The method of collecting the partial discharge digital data stream of the power distribution switch cabinet includes: Collect partial discharge simulation signals from distribution switch cabinets; Performing denoising processing on the partial discharge simulation signal to obtain a target partial discharge simulation signal; The target partial discharge signal is converted into a partial discharge digital data stream.

5. The method according to claim 4, characterized in that The denoising process is performed on the partial discharge simulation signal to obtain a target partial discharge simulation signal, including: Performing wavelet decomposition of multiple scales on the partial discharge simulation signal to obtain wavelet coefficients of multiple scales; Perform coefficient denoising on the wavelet coefficients of the multiple scales based on a preset analysis threshold to obtain target wavelet coefficients; The target partial discharge simulation signal is obtained by performing inverse wavelet transform reconstruction based on the target wavelet coefficients.

6. The method according to claim 4, characterized in that The step of converting the target partial discharge signal into a partial discharge digital data stream comprises: extracting the pulse frequency of the target partial discharge signal; Determine the capture bandwidth of the analog-to-digital conversion device according to the pulse frequency and the preset magnification; The target partial discharge signal is converted into a partial discharge digital data stream by the analog-to-digital conversion device based on the capture bandwidth.

7. A remote monitoring device for a power distribution switch cabinet, characterized in that: The remote monitoring device of the power distribution switch cabinet comprises: A collection module is used to collect the partial discharge digital data stream of the distribution switch cabinet; A generating module, used for generating a discharge phase distribution spectrum based on the partial discharge digital data stream; An identification module, used for performing spectrum recognition based on the discharge phase distribution spectrum through a trained partial discharge defect detection model to obtain a spectrum feature probability set; An output module is used to output a remote detection report of the distribution switch cabinet according to the graph feature probability set.

8. A remote monitoring device for a power distribution switch cabinet, characterized in that: The remote monitoring device of the distribution switch cabinet includes: a memory, a processor, and a remote monitoring program of the distribution switch cabinet stored in the memory and executable on the processor. The remote monitoring program of the distribution switch cabinet is configured to implement the steps of the remote monitoring method of the distribution switch cabinet as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores a remote monitoring program for a distribution switch cabinet, and when the remote monitoring program for a distribution switch cabinet is executed by a processor, the steps of the remote monitoring method for a distribution switch cabinet according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the remote monitoring method for a power distribution switch cabinet according to any one of claims 1 to 6 are implemented.

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