Equipment insulation state determination method and device and nonvolatile storage medium

Abstract

The invention discloses an equipment insulation state determination method and device and a nonvolatile storage medium. The method comprises the following steps: acquiring an initial pulse signal of target equipment; based on the initial pulse signal, determining the discharge capacity corresponding to the target equipment; separating the initial pulse signal to obtain a target pulse signal; converting the target pulse signal into polar coordinates; based on the polar coordinates, determining a target polar coordinate vector domain distribution diagram corresponding to the target pulse signal; determining a target signal type corresponding to the target polar coordinate vector domain distribution diagram based on a preset corresponding relationship between a plurality of candidate polar coordinate vector domain distribution diagrams and a plurality of signal types; and determining the insulation state of the target equipment based on the target signal type and the discharge capacity. According to the invention, the technical problem that the insulation defect detection of power equipment is not accurate enough due to the weak anti-interference capability of current partial discharge monitoring in a complex electromagnetic environment is solved.

Description

Technical Field

[0001] This invention relates to the field of power detection technology, and more specifically, to a method, apparatus, and non-volatile storage medium for determining the insulation status of equipment. Background Technology

[0002] In the field of power equipment maintenance and monitoring, partial discharge detection is a key technology for assessing the insulation condition of power equipment such as power cables, transformers, and reactors. Partial discharge often occurs at insulation defects in power equipment. When the electric field strength reaches the breakdown field strength of that area, especially under test or rated voltage, it can cause local breakdown of the insulation material, generating a small amount of discharge energy. Although this energy is small, it indicates potential problems in the insulation system of the power equipment. Long-term discharge can lead to the deterioration of the insulation material, potentially causing complete equipment failure. Therefore, timely detection and identification of partial discharge types are of great significance for preventing power equipment failures and ensuring the safe operation of the power system.

[0003] Current methods for partial discharge interference suppression and discharge type identification technologies have shortcomings in terms of signal extraction accuracy, signal type identification efficiency, and data processing in complex electromagnetic environments. In complex electromagnetic environments, especially when the frequency of the interference signal overlaps with the frequency of the partial discharge signal, accurately selecting the frequency range becomes extremely difficult. This not only leads to attenuation of the actual partial discharge signal but may also introduce additional interference noise, reducing detection accuracy and sensitivity. Furthermore, when the frequency of periodic interference changes in the field, manual adjustment of the frequency threshold is required, which limits the adaptability and practicality of the methods.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method, apparatus, and non-volatile storage medium for determining the insulation state of equipment, in order to at least solve the technical problem that current partial discharge monitoring has weak anti-interference capability in complex electromagnetic environments, resulting in inaccurate detection of insulation defects in power equipment.

[0006] According to one aspect of the present invention, a method for determining the insulation state of a device is provided, comprising: acquiring an initial pulse signal of a target device; determining the discharge quantity corresponding to the target device based on the initial pulse signal; separating the initial pulse signal to obtain a target pulse signal; converting the target pulse signal into polar coordinates; determining a target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; determining a target signal type corresponding to the target polar coordinate vector domain distribution map based on a preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types; and determining the insulation state of the target device based on the target signal type and the discharge quantity.

[0007] Optionally, the initial pulse signal is separated to obtain the target pulse signal, including: filtering the pulse signal to obtain a processed pulse signal; performing a Fourier transform on the processed pulse signal to determine the time-frequency characteristics corresponding to the processed pulse signal; and separating the processed pulse signal based on the time-frequency characteristics to obtain the target pulse signal.

[0008] Optionally, converting the target pulse signal into polar coordinates includes: determining a target pulse signal sequence based on the target pulse signal; extracting multiple sampling points that meet preset conditions from the target pulse signal sequence based on a preset signal sampling interval; calculating the complex representation of the target pulse signal sequence at the multiple sampling points; and determining polar coordinates based on the complex representation at the multiple sampling points.

[0009] Optionally, based on the pre-defined correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types, the target signal type corresponding to the target polar coordinate vector domain distribution map is determined, including: calculating the cross-correlation coefficients between the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps; and selecting the signal type corresponding to the candidate polar coordinate vector domain distribution map whose cross-correlation coefficients satisfy a pre-defined condition as the target signal type.

[0010] Optionally, based on a preset formula, the cross-correlation coefficients between the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps are calculated, wherein the preset formula is as follows:

[0011] ,

[0012] in, For cross-correlation coefficients, The target polar coordinate vector domain distribution map, For any one of the multiple candidate polar coordinate vector domain distribution maps, The average value of the target pulse signal. This represents the average value of the pulse signal corresponding to the candidate polar coordinate vector domain distribution map. For the preset signal sampling index, This is the preset signal sampling length.

[0013] Optionally, the insulation status of the target device is determined based on the target signal type and discharge quantity, including: determining the insulation status of the target device as normal when the target signal type is a noise signal type.

[0014] Optionally, the insulation state of the target device is determined based on the target signal type and the discharge quantity, including: if the target signal type is a discharge signal type, determining that the insulation state of the target device is that there is an insulation defect; if the insulation state is that there is an insulation defect, determining the degree of insulation defect of the target device based on the discharge quantity.

[0015] According to another aspect of the present invention, a device for determining the insulation state of a device is also provided, comprising: an acquisition module for acquiring an initial pulse signal of a target device; a first determination module for determining the discharge quantity corresponding to the target device based on the initial pulse signal; a separation module for separating the initial pulse signal to obtain a target pulse signal; a conversion module for converting the target pulse signal into polar coordinates; a second determination module for determining a target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; a third determination module for determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on a preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types; and a fourth determination module for determining the insulation state of the target device based on the target signal type and the discharge quantity.

[0016] According to another aspect of the present invention, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored program, wherein, when the program is running, it controls the device where the non-volatile storage medium is located to execute any of the above-described device insulation state determination methods.

[0017] According to another aspect of the present invention, a computer device is also provided, the computer device including a processor, the processor being configured to run a program, wherein the program executes any of the above-described methods for determining the insulation state of a device.

[0018] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements any of the above-described methods for determining the insulation state of a device.

[0019] In this embodiment of the invention, a method for determining the insulation state of a device is employed. This involves acquiring an initial pulse signal of the target device; determining the discharge quantity corresponding to the target device based on the initial pulse signal; separating the initial pulse signal to obtain a target pulse signal; converting the target pulse signal into polar coordinates; determining the target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on the pre-set correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types; and determining the insulation state of the target device based on the target signal type and the discharge quantity. This achieves the purpose of separating the pulse signal, thereby improving the accuracy of insulation state detection and solving the technical problem that current partial discharge monitoring has weak anti-interference capabilities in complex electromagnetic environments, leading to inaccurate detection of insulation defects in power equipment. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0021] Figure 1 A hardware block diagram of a computer terminal for implementing a method for determining the insulation state of a device is shown.

[0022] Figure 2 This is a flowchart illustrating the method for determining the insulation state of a device according to an embodiment of the present invention;

[0023] Figure 3 This is a sample image of the white noise polar coordinate vector domain provided by an optional embodiment of the present invention;

[0024] Figure 4 This is a sample diagram of the corona discharge electrode coordinate vector domain provided by an optional embodiment of the present invention;

[0025] Figure 5 This is a structural block diagram of a device for determining the insulation status of an equipment according to an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] According to an embodiment of the present invention, a method embodiment for determining the insulation state of a device is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing a method for determining the insulation state of a device is shown. Figure 1 As shown, the computer terminal 10 may include one or more processors (shown as 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0030] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0031] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the device insulation state determination method in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the device insulation state determination method of the aforementioned application. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0032] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0033] Figure 2 This is a flowchart illustrating the method for determining the insulation state of a device according to an embodiment of the present invention, as shown below. Figure 2 As shown, the method includes the following steps:

[0034] Step S202: Obtain the initial pulse signal of the target device.

[0035] In this step, a suitable partial discharge sensing device can be selected for the target equipment (such as high-voltage cables, transformers, motors, etc.). This typically includes, but is not limited to, high-frequency current sensors, ultrasonic sensors, radio frequency sensors, or optical sensors. The most appropriate detection method should be selected based on the nature of the equipment and its operating environment. The selected sensor should be installed at an appropriate location on the target equipment to ensure effective capture of the pulse signals generated by partial discharge. The parameters of the signal acquisition system should be set, including sampling rate, bandwidth, gain, and trigger conditions, to ensure that the quality of the acquired signal meets the analysis requirements. A high sampling rate helps capture signal details, and appropriate bandwidth prevents the loss of important information. The signal acquisition device should be started to collect pulse signals from the target equipment in real time or periodically during its operation.

[0036] Step S204: Determine the discharge amount corresponding to the target device based on the initial pulse signal.

[0037] In this step, the acquired initial pulse signal can be preprocessed, including but not limited to noise reduction, smoothing, and normalization. The purpose of preprocessing is to eliminate interference, making the signal more suitable for analysis, and ensuring the accuracy of discharge calculation in subsequent steps. The discharge amount can be estimated by integrating the pulse signal. Common integration methods include full-wave integration and half-wave integration. For each identified pulse, integrating the amplitude of its waveform yields the corresponding discharge amount. If the signal has been digitized, the discharge amount can be approximated by summing the pulse amplitude sequence and multiplying it by the sampling time interval.

[0038] Step S206: Separate the initial pulse signal to obtain the target pulse signal.

[0039] In this step, because different types of signals will form different point clusters on the time-frequency distribution spectrum, different types of noise and discharge signals can be separated based on the time-frequency distribution of the pulse signal. Techniques such as Short-Time Fourier Transform (STFT), Wavelet Transform, or Hilbert-Huang Transform (HHT) can be used to decompose the signal in the time and frequency domains, identifying the characteristic frequencies and time windows of the partial discharge pulses. Pulse detection algorithms, such as threshold detection, morphological matching, or adaptive pulse detection, are applied to separate individual partial discharge pulse events from the time-frequency analysis results. By establishing an interference signal database, interference unrelated to the partial discharge signal, such as switching actions, power grid harmonics, and radio frequency interference, is identified and filtered out to ensure the purity of the target signal.

[0040] If multiple sensors are used for signal acquisition, time synchronization is required to ensure that pulse signals acquired from different locations are aligned for comparison and analysis.

[0041] By following the steps above, the target pulse signal, i.e. the signal related to partial discharge, can be effectively separated from the initial pulse signal, providing key information for further discharge quantity assessment, insulation condition diagnosis, and equipment maintenance decisions.

[0042] Step S208: Convert the target pulse signal into polar coordinates.

[0043] In this step, the target pulse signal can be appropriately sampled and quantized to obtain a series of discrete time-series data points, each containing the instantaneous amplitude of the signal. Then, the signal index interval and the number of dimensions are defined. Typically, the signal index interval can be set to an integer multiple of the signal sampling period to ensure that the periodicity and continuity of the signal are preserved. The number of dimensions is determined based on the complexity of the required analysis. For each sampling point, its polar coordinate vector elements in multidimensional space are calculated. With the positions of each sampling point in multidimensional space, these sampling points can be transformed from a Cartesian coordinate system to a polar coordinate system.

[0044] Step S210: Based on polar coordinates, determine the target polar coordinate vector domain distribution map corresponding to the target pulse signal.

[0045] In this step, a polar coordinate vector domain distribution map can be drawn using 3D plotting software or tools based on the calculated polar coordinates of multiple sampling points. In the map, the position and density of each point can reflect the distribution characteristics of the pulse signal in different directions, as well as the changes in signal strength.

[0046] Through the above steps, the target pulse signal can be converted and visualized as a polar coordinate vector domain distribution map, providing an intuitive graphical representation for partial discharge monitoring and insulation status assessment of power equipment.

[0047] Step S212: Based on the preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types, determine the target signal type corresponding to the target polar coordinate vector domain distribution map.

[0048] In this step, a sample library of polar coordinate vector domain distribution maps containing various signal types is constructed. Each signal type (such as corona discharge, internal discharge, surface discharge, levitational discharge, and metal particle discharge) has its unique polar coordinate vector distribution pattern. The sample library should include distribution maps of various common noise signals (such as white noise, switching interference, periodic interference, and radio frequency interference) and discharge signals. For the target polar coordinate vector domain distribution map, the cross-correlation coefficient between it and the distribution maps of each signal type in the sample library is calculated. The cross-correlation coefficient can be used to measure the similarity between two signals, and its value is usually between 0 and 1.

[0049] From all the calculated cross-correlation coefficients, find the sample signal corresponding to the maximum value. The signal type represented by this sample signal is the type of the target signal. This is because the sample with the largest cross-correlation coefficient indicates that it has the highest similarity to the target signal.

[0050] Through the above steps, the type of target signal can be accurately determined based on the polar coordinate vector domain distribution map and cross-correlation coefficient analysis, enabling effective monitoring and evaluation of the status of power equipment.

[0051] Step S214: Determine the insulation status of the target device based on the target signal type and discharge quantity.

[0052] In this step, if the signal is identified as noise and the discharge level is below the preset background noise level, it can be preliminarily determined that the equipment's insulation condition is good. When the signal is identified as a partial discharge and the discharge level exceeds a certain multiple (e.g., 2 times) of the background noise level, this indicates that the equipment may have a minor insulation defect. If the signal discharge level further increases, reaching a higher multiple (e.g., 4 times) of the background noise level, the equipment may have a serious insulation problem, requiring immediate attention and further diagnosis.

[0053] Based on the results of the insulation condition assessment, a detailed report can be generated with corresponding recommendations. For example, if the insulation condition is considered normal, the report may recommend continued monitoring; if potential insulation problems are detected, the report may include recommended maintenance actions, such as preventative repairs or replacement of the problematic component.

[0054] This method separates different types of noise and discharge signals based on the time-frequency distribution of pulse signals, solving the problem of accurately distinguishing partial discharge from various interference signals in complex electromagnetic environments. By standardizing the acquired signals and calculating the time center, equivalent time, and frequency, the distribution characteristics of different signal types can be intuitively observed on the time-frequency distribution spectrum, thus effectively separating partial discharge and interference components in the pulse signal. Furthermore, the separated pulse signal is converted into a polar coordinate vector, and a polar coordinate vector domain distribution map is plotted. The distribution characteristics of the signal in polar coordinate space are used for identification, avoiding the problems of traditional anti-interference methods in determining the signal frequency range and signal distortion, significantly improving the anti-interference capability of partial discharge detection. Based on multiple preset candidate polar coordinate vector domain distribution maps and the correspondence between multiple signal types, the signal type is quickly and accurately identified by calculating the cross-correlation coefficient, without the need for complex calculation processes or additional hardware investment, effectively overcoming the shortcomings of artificial neural networks such as high computational load and data redundancy. Finally, by combining the signal type identification results and discharge quantity, the insulation status of power equipment is determined, achieving efficient and accurate assessment of the insulation status of power equipment. This technical solution reduces on-site testing wiring and simplifies the insulation condition assessment process, which is of great significance for timely detection of insulation hazards in power equipment and ensuring the safe and stable operation of the power system.

[0055] Through the above steps, the pulse signal can be separated, thereby improving the accuracy of insulation condition detection. This solves the technical problem that the current partial discharge monitoring has weak anti-interference ability in complex electromagnetic environments, which leads to inaccurate detection of insulation defects in power equipment.

[0056] As an optional embodiment, separating the initial pulse signal to obtain the target pulse signal includes: filtering the pulse signal to obtain a processed pulse signal; performing a Fourier transform on the processed pulse signal to determine the time-frequency characteristics corresponding to the processed pulse signal; and separating the processed pulse signal based on the time-frequency characteristics to obtain the target pulse signal.

[0057] Optionally, the process of separating the initial pulse signal to obtain the target pulse signal includes filtering, Fourier transform, and signal separation based on time-frequency characteristics. First, the acquired pulse signal is filtered to eliminate noise and interference in specific frequency bands, resulting in a relatively clean signal. Then, Fourier transform technology is used to convert the processed signal from the time domain to the frequency domain, revealing the signal's time-frequency characteristics and providing a basis for subsequent signal separation. Based on the signal's time-frequency characteristics, a separation algorithm is used to distinguish the target pulse signal from background noise, ensuring accurate extraction of the target signal.

[0058] Specifically, the real-time acquired signal s(t) can be standardized based on the following formula to obtain the processed signal. :

[0059] .

[0060] Then calculate the signal time center. ,in, .

[0061] Calculate the equivalent time of the signal according to the following formulas. and equivalent frequency :

[0062] ;

[0063] ;

[0064] in, For standardized pulse signals The Fourier transform is used. The equivalent time represents the change of the pulse signal relative to the time centroid, and the equivalent frequency represents the change of the pulse signal relative to the frequency centroid. The transformed signal is determined, and then the time-frequency features of the signal are extracted.

[0065] Through the above steps, this embodiment can effectively combat interference in complex electromagnetic environments, improve the accuracy of partial discharge detection, and facilitate the precise assessment of the insulation status of power equipment.

[0066] As an optional embodiment, converting the target pulse signal into polar coordinates includes: determining a target pulse signal sequence based on the target pulse signal; extracting multiple sampling points that meet preset conditions from the target pulse signal sequence based on a preset signal sampling interval; calculating the complex representation of the target pulse signal sequence at the multiple sampling points; and determining polar coordinates based on the complex representation at the multiple sampling points.

[0067] Optionally, the signal sequence of the target pulse signal can be determined based on the target pulse signal; then, according to the preset signal sampling interval, multiple sampling points that meet specific conditions are accurately extracted from the signal sequence; next, the complex representation of the target pulse signal sequence at these sampling points is calculated; finally, the polar coordinates of the target pulse signal are determined based on the complex representation of the sampling points.

[0068] Specifically, for the target pulse signal, its signal sequence is obtained as follows:

[0069] ,

[0070] in, For signal sampling index, This represents the signal sampling length.

[0071] Then calculate the polar coordinate vector of the pulse signal:

[0072] ,

[0073] in, For signal index intervals; For the number of dimensions, For dimensional indexing, It is a unit vector. When m=2, the time-domain signal can be converted into a two-dimensional spatial polar coordinate distribution; when m=3, the time-domain signal can be converted into a three-dimensional spatial polar coordinate distribution.

[0074] By converting time-domain signals to polar coordinates, not only can different types of partial discharge signals and noise be effectively separated, but the signal source type can also be quickly identified based on the polar coordinate vector distribution of the signal without increasing additional hardware costs or field wiring complexity. This improves the accuracy and efficiency of power equipment insulation condition assessment. In practical applications, this technical process ensures the accurate extraction and identification of partial discharge signals from complex electromagnetic environments, providing crucial protection for the safe operation of power equipment.

[0075] As an optional embodiment, the target signal type corresponding to the target polar coordinate vector domain distribution map is determined based on the preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types. This includes: calculating the cross-correlation coefficients between the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps; and selecting the signal type corresponding to the candidate polar coordinate vector domain distribution map whose cross-correlation coefficients satisfy preset conditions as the target signal type.

[0076] Optionally, the correlation coefficients between the target polar coordinate vector domain distribution map and multiple candidate polar coordinate vector domain distribution maps are calculated. By comparing these correlation coefficients, the signal type represented by the candidate polar coordinate vector domain distribution map that meets the preset condition (i.e., the maximum correlation coefficient) is selected as the target signal type. This design aims to achieve accurate identification of the separated signal type through quantitative comparison, ensuring the accuracy of the insulation status assessment of power equipment. By comparing with typical signal distributions in the sample library, the signal source can be quickly identified, improving assessment efficiency and reducing misjudgments caused by incorrect signal type identification, thus ensuring the safe operation of power equipment.

[0077] Specifically, a polar coordinate vector domain sample library of typical noise signals and a polar coordinate vector domain sample library of typical discharge signals can be constructed for matching. The sample library can include white noise, switching interference, periodic interference, and radio frequency interference. Figure 3 This is a sample image of white noise polar coordinate vector domain provided by an optional embodiment of the present invention. Then, a sample library of typical discharge signals in polar coordinate vector domain can be constructed, including corona discharge, internal discharge, surface discharge, suspension discharge, and metal particle discharge, wherein... Figure 4 This is a sample diagram of the coordinate vector domain of the corona discharge electrode provided according to an optional embodiment of the present invention.

[0078] As an optional embodiment, based on a preset formula, the cross-correlation coefficients corresponding to the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps are calculated, wherein the preset formula is as follows:

[0079] ,

[0080] in, For cross-correlation coefficients, The target polar coordinate vector domain distribution map, For any one of the multiple candidate polar coordinate vector domain distribution maps, The average value of the target pulse signal. This represents the average value of the pulse signal corresponding to the candidate polar coordinate vector domain distribution map. For the preset signal sampling index, This is the preset signal sampling length.

[0081] As an optional embodiment, the insulation status of the target device is determined based on the target signal type and discharge quantity, including: determining the insulation status of the target device as normal when the target signal type is a noise signal type.

[0082] As an optional embodiment, determining the insulation state of the target device based on the target signal type and discharge quantity includes: determining that the insulation state of the target device has an insulation defect when the target signal type is a discharge signal type; and determining the degree of insulation defect of the target device based on the discharge quantity when the insulation state has an insulation defect.

[0083] Optionally, when the signal type is identified as a noise signal, the electrical equipment is considered to have good insulation; when the signal type is identified as a discharge signal and the discharge amount is greater than twice the background noise, the electrical equipment is considered to have insulation defects; when the signal type is identified as a discharge signal and the discharge amount is greater than four times the background noise, the electrical equipment is considered to have serious insulation defects.

[0084] This embodiment enables accurate assessment of the insulation status of power equipment, making early detection and graded warning of insulation defects possible, and effectively improving the safety and reliability of power equipment operation.

[0085] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0086] Through the above description of the embodiments, those skilled in the art can clearly understand that the device insulation state determination method according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0087] According to embodiments of the present invention, an apparatus for determining the insulation state of equipment for implementing the above-described method for determining the insulation state of equipment is also provided. Figure 5This is a structural block diagram of a device for determining the insulation state according to an embodiment of the present invention, such as... Figure 5 As shown, the device for determining the insulation status of the equipment includes: an acquisition module 502, a first determination module 504, a separation module 506, a conversion module 508, a second determination module 510, a third determination module 512, and a fourth determination module 514. The device for determining the insulation status of the equipment will be described below.

[0088] The acquisition module 502 is used to acquire the initial pulse signal of the target device.

[0089] The first determining module 504, connected to the acquiring module 502, is used to determine the discharge amount corresponding to the target device based on the initial pulse signal.

[0090] The separation module 506 is connected to the first determining module 504 and is used to separate the initial pulse signal to obtain the target pulse signal.

[0091] The conversion module 508, connected to the separation module 506, is used to convert the target pulse signal into polar coordinates.

[0092] The second determining module 510, connected to the conversion module 508, is used to determine the target polar coordinate vector domain distribution map corresponding to the target pulse signal based on polar coordinates.

[0093] The third determining module 512, connected to the second determining module 510, is used to determine the target signal type corresponding to the target polar coordinate vector domain distribution map based on the preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types.

[0094] The fourth determining module 514, connected to the third determining module 512, is used to determine the insulation status of the target device based on the target signal type and discharge quantity.

[0095] It should be noted that the aforementioned acquisition module 502, first determination module 504, separation module 506, conversion module 508, second determination module 510, third determination module 512, and fourth determination module 514 correspond to steps S202 to S214 in the embodiments. Multiple modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should also be noted that the aforementioned modules, as part of the device, can run on the computer terminal 10 provided in the embodiments.

[0096] Embodiments of the present invention may provide a computer device. Optionally, in this embodiment, the computer device may be located in at least one of a plurality of network devices in a computer network. The computer device includes a memory and a processor.

[0097] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the device insulation state determination method and apparatus in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned device insulation state determination method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0098] The processor can access information and application programs stored in the memory via a transmission device to perform the following steps: acquiring the initial pulse signal of the target device; determining the discharge quantity corresponding to the target device based on the initial pulse signal; separating the initial pulse signal to obtain the target pulse signal; converting the target pulse signal into polar coordinates; determining the target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on the correspondence between multiple preset candidate polar coordinate vector domain distribution maps and multiple signal types; and determining the insulation state of the target device based on the target signal type and the discharge quantity.

[0099] Optionally, the processor may also execute program code for the following steps: separating the initial pulse signal to obtain the target pulse signal, including: filtering the pulse signal to obtain the processed pulse signal; performing a Fourier transform on the processed pulse signal to determine the time-frequency characteristics corresponding to the processed pulse signal; and separating the processed pulse signal based on the time-frequency characteristics to obtain the target pulse signal.

[0100] Optionally, the processor may also execute program code for the following steps: converting the target pulse signal into polar coordinates, including: determining a target pulse signal sequence based on the target pulse signal; extracting multiple sampling points that meet preset conditions from the target pulse signal sequence based on a preset signal sampling interval; calculating the complex representation of the target pulse signal sequence at the multiple sampling points; and determining polar coordinates based on the complex representation at the multiple sampling points.

[0101] Optionally, the processor may also execute program code for the following steps: determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on the preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types, including: calculating the cross-correlation coefficients corresponding to the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps respectively; selecting the signal type corresponding to the candidate polar coordinate vector domain distribution map whose cross-correlation coefficients satisfy preset conditions as the target signal type.

[0102] Optionally, the processor may also execute program code that performs the following steps: Based on a preset formula, calculate the cross-correlation coefficients between the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps, wherein the preset formula is as follows:

[0103] ,

[0104] in, For cross-correlation coefficients, The target polar coordinate vector domain distribution map, For any one of the multiple candidate polar coordinate vector domain distribution maps, The average value of the target pulse signal. This represents the average value of the pulse signal corresponding to the candidate polar coordinate vector domain distribution map. For the preset signal sampling index, This is the preset signal sampling length.

[0105] Optionally, the processor may also execute program code that performs the following steps: determining the insulation status of the target device based on the target signal type and discharge quantity, including: determining the insulation status of the target device to be normal when the target signal type is a noise signal type.

[0106] Optionally, the processor may also execute program code for the following steps: determining the insulation state of the target device based on the target signal type and discharge quantity, including: determining that the insulation state of the target device is an insulation defect when the target signal type is a discharge signal type; and determining the degree of insulation defect of the target device based on the discharge quantity when the insulation state is an insulation defect.

[0107] This invention provides a method for determining the insulation state of a device. The method involves: acquiring an initial pulse signal of the target device; determining the discharge quantity corresponding to the target device based on the initial pulse signal; separating the initial pulse signal to obtain a target pulse signal; converting the target pulse signal into polar coordinates; determining the target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on a preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types; and determining the insulation state of the target device based on the target signal type and the discharge quantity. This method achieves the purpose of separating the pulse signal, thereby improving the accuracy of insulation state detection and solving the technical problem that current partial discharge monitoring has weak anti-interference capabilities in complex electromagnetic environments, leading to inaccurate detection of insulation defects in power equipment.

[0108] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a non-volatile storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0109] Embodiments of the present invention also provide a non-volatile storage medium. Optionally, in this embodiment, the non-volatile storage medium can be used to store the program code executed by the device insulation state determination method provided in the above embodiments.

[0110] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0111] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: acquiring an initial pulse signal of the target device; determining the discharge quantity corresponding to the target device based on the initial pulse signal; separating the initial pulse signal to obtain a target pulse signal; converting the target pulse signal into polar coordinates; determining the target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on the preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types; and determining the insulation state of the target device based on the target signal type and the discharge quantity.

[0112] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: separating the initial pulse signal to obtain the target pulse signal, including: filtering the pulse signal to obtain a processed pulse signal; performing a Fourier transform on the processed pulse signal to determine the time-frequency characteristics corresponding to the processed pulse signal; and separating the processed pulse signal based on the time-frequency characteristics to obtain the target pulse signal.

[0113] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: converting the target pulse signal into polar coordinates, including: determining a target pulse signal sequence based on the target pulse signal; extracting multiple sampling points that meet preset conditions from the target pulse signal sequence based on a preset signal sampling interval; calculating the complex representation of the target pulse signal sequence at the multiple sampling points; and determining polar coordinates based on the complex representation at the multiple sampling points.

[0114] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on the preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types, including: calculating the cross-correlation coefficients corresponding to the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps respectively; selecting the signal type corresponding to the candidate polar coordinate vector domain distribution map whose cross-correlation coefficients satisfy preset conditions as the target signal type.

[0115] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: calculating the cross-correlation coefficients between the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps based on a preset formula, wherein the preset formula is as follows:

[0116] ,

[0117] in, For cross-correlation coefficients, The target polar coordinate vector domain distribution map, For any one of the multiple candidate polar coordinate vector domain distribution maps, The average value of the target pulse signal. This represents the average value of the pulse signal corresponding to the candidate polar coordinate vector domain distribution map. For the preset signal sampling index, This is the preset signal sampling length.

[0118] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the insulation state of the target device based on the target signal type and discharge quantity, including: determining that the insulation state of the target device is normal when the target signal type is a noise signal type.

[0119] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the insulation state of the target device based on the target signal type and the discharge quantity, including: determining that the insulation state of the target device has an insulation defect when the target signal type is a discharge signal type; and determining the degree of insulation defect of the target device based on the discharge quantity when the insulation state has an insulation defect.

[0120] Embodiments of the present invention also provide a computer program product, including a computer program. Optionally, in this embodiment, when the computer program is executed by a processor, it can perform the following: acquiring an initial pulse signal of a target device; determining the discharge quantity corresponding to the target device based on the initial pulse signal; separating the initial pulse signal to obtain a target pulse signal; converting the target pulse signal into polar coordinates; determining a target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; determining the target signal type corresponding to the target polar coordinate vector domain distribution map based on a preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types; and determining the insulation state of the target device based on the target signal type and the discharge quantity.

[0121] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0122] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0124] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0125] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0126] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0127] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining the insulation state of equipment, characterized in that, include: Acquire the initial pulse signal of the target device; Based on the initial pulse signal, the discharge amount corresponding to the target device is determined; The initial pulse signal is separated to obtain the target pulse signal; Convert the target pulse signal into polar coordinates; Based on the polar coordinates, determine the target polar coordinate vector domain distribution map corresponding to the target pulse signal; Based on the pre-defined correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types, the target signal type corresponding to the target polar coordinate vector domain distribution map is determined; The insulation state of the target device is determined based on the target signal type and the discharge quantity.

2. The method according to claim 1, characterized in that, The step of separating the initial pulse signal to obtain the target pulse signal includes: The pulse signal is filtered to obtain the processed pulse signal; Perform a Fourier transform on the processed pulse signal to determine the time-frequency characteristics corresponding to the processed pulse signal; Based on the time-frequency characteristics, the processed pulse signal is separated to obtain the target pulse signal.

3. The method according to claim 1, characterized in that, The step of converting the target pulse signal into polar coordinates includes: Based on the target pulse signal, determine the target pulse signal sequence; Based on a preset signal sampling interval, multiple sampling points that meet preset conditions are extracted from the target pulse signal sequence; Calculate the complex representation of the target pulse signal sequence at the plurality of sampling points; The polar coordinates are determined based on the complex representations at the multiple sampling points.

4. The method according to claim 1, characterized in that, The determination of the target signal type corresponding to the target polar coordinate vector domain distribution map based on the pre-defined correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types includes: Calculate the cross-correlation coefficients between the target polar coordinate vector domain distribution map and each of the multiple candidate polar coordinate vector domain distribution maps; The signal type corresponding to the candidate polar coordinate vector domain distribution map whose cross-correlation coefficient satisfies the preset condition is selected as the target signal type.

5. The method according to claim 4, characterized in that, Based on a preset formula, the cross-correlation coefficients corresponding to the target polar coordinate vector domain distribution map and the multiple candidate polar coordinate vector domain distribution maps are calculated, wherein the preset formula is as follows: ， in, For cross-correlation coefficients, This is a distribution map of the polar coordinate vector domain of the target. For any one of the multiple candidate polar coordinate vector domain distribution maps, The average value of the target pulse signal. This represents the average value of the pulse signal corresponding to the candidate polar coordinate vector domain distribution map. For the preset signal sampling index, This is the preset signal sampling length.

6. The method according to any one of claims 1 to 5, characterized in that, Determining the insulation state of the target device based on the target signal type and the discharge quantity includes: If the target signal type is a noise signal type, the insulation status of the target device is determined to be normal.

7. The method according to any one of claims 1 to 5, characterized in that, Determining the insulation state of the target device based on the target signal type and the discharge quantity includes: If the target signal type is a discharge signal type, the insulation state of the target device is determined to be that there is an insulation defect. When the insulation condition indicates the presence of insulation defects, the degree of insulation defect in the target device is determined based on the discharge quantity.

8. A device for determining the insulation state of equipment, characterized in that, include: The acquisition module is used to acquire the initial pulse signal of the target device; The first determining module is used to determine the discharge amount corresponding to the target device based on the initial pulse signal; A separation module is used to separate the initial pulse signal to obtain the target pulse signal; A conversion module is used to convert the target pulse signal into polar coordinates; The second determining module is used to determine the target polar coordinate vector domain distribution map corresponding to the target pulse signal based on the polar coordinates; The third determining module is used to determine the target signal type corresponding to the target polar coordinate vector domain distribution map based on the preset correspondence between multiple candidate polar coordinate vector domain distribution maps and multiple signal types; The fourth determining module is used to determine the insulation state of the target device based on the target signal type and the discharge quantity.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the non-volatile storage medium to perform the device insulation state determination method according to any one of claims 1 to 7.

10. A computer device, characterized in that, include: Memory and processor The memory stores computer programs; The processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, the processor performs the device insulation state determination method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the device insulation state determination method according to any one of claims 1 to 7.

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