A partial discharge detection method, device and storage medium

Abstract

The present invention relates to the field of power system equipment maintenance, and in particular to a partial discharge detection method, device and storage medium. The method is aimed at ultra-short rise time square wave high electric field. After obtaining partial discharge signal data and interference signal data, the corresponding spectrum characteristics are extracted, and the spectrum difference between the partial discharge signal and the interference signal is calculated; the first frequency interval when the spectrum difference is greater than the first threshold is calculated, and the signal outside the corresponding first frequency interval is filtered to obtain the filtered partial discharge signal and the residual interference signal, and the first threshold is determined by the spectrum difference; based on the filtered partial discharge signal, the residual interference signal and the pre-set spectrum difference database, the second frequency interval is predicted, and the second frequency interval is adjusted by a negative feedback mechanism to extract the partial discharge signal under the highest signal-to-noise ratio. Compared with the prior art, the present invention has the advantages of improving the anti-interference ability in the PD detection process, effectively suppressing interference and improving the stability of PD signal extraction.

Description

Technical Field

[0001] The present invention relates to the field of power system equipment maintenance, and in particular to a partial discharge detection method, device and storage medium. Background Art

[0002] The converter station is an important key equipment in the power system, mainly used to convert AC power into DC power, and plays a vital role in the UHV transmission system. However, there is also the problem of partial discharge (PD) in the insulation of the converter station equipment. PD not only increases the failure rate and maintenance cost of the equipment, but also has an adverse effect on the normal operation of the power system. Therefore, in view of the difficulties in detecting partial discharge in the converter station, it is necessary to continuously promote the research and development and innovation of PD detection technology, improve the accuracy and reliability of detection, and strengthen safety protection measures under high-voltage environments to ensure the normal operation of the converter station and the long life of the equipment. The PD signal in the converter station is usually very weak and is affected by noise and interference. Therefore, it is necessary to develop effective signal processing and analysis methods to filter, gain adjust, and extract features on the PD signal to accurately determine the presence and degree of partial discharge.

[0003] Traditional PD detection technologies mainly include pulse current method, ultrasonic detection method, electromagnetic wave detection method, etc. These methods have their own limitations, such as the inability to monitor in real time, low detection accuracy, and poor anti-interference. As an important node in the power system, the converter station has a complex working environment and high voltage and current levels. In particular, the output of power electronic devices in the converter station is usually a square wave high voltage with a short rise time. The rapid change of the electric field at the rising and falling edges will cause large displacement current and electromagnetic pulse interference, which may make it difficult to distinguish between local discharge signals and interference. Therefore, how to improve the anti-interference ability and stability of PD detection in the converter station to ensure reliable detection results has become a problem that needs to be solved in this field. Summary of the invention

[0004] The purpose of the present invention is to provide a partial discharge detection method, device and storage medium in order to overcome the defects of the above-mentioned prior art. The method targets a square wave high electric field with an ultra-short rise time, performs real-time spectrum analysis on interference signals and partial discharge signals under the electric field, adjusts the passband of the digital filter through an adaptive control system, and maximizes the signal-to-noise ratio of partial discharge signal extraction, which can effectively improve the anti-interference ability and stability of partial discharge detection.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] According to a first aspect of the present invention, there is provided a partial discharge detection method, the method comprising the following steps:

[0007] S1, obtaining partial discharge signal data and interference signal data, extracting corresponding frequency spectrum features, and calculating the frequency spectrum difference between the partial discharge signal and the interference signal;

[0008] S2, calculating a first frequency interval when the frequency spectrum difference between the partial discharge signal and the interference signal is greater than a first threshold, filtering signals outside the first frequency interval, and obtaining a filtered partial discharge signal and a residual interference signal, wherein the first threshold is determined by the frequency spectrum difference between the partial discharge signal and the interference signal;

[0009] S3, predicting a second frequency interval based on the filtered partial discharge signal, the residual interference signal and the spectrum difference database, and adjusting the second frequency interval using a negative feedback mechanism to extract the partial discharge signal under the highest signal-to-noise ratio, wherein the spectrum difference database is preset.

[0010] As a preferred technical solution, the spectrum difference database is continuous, and the spectrum difference database includes calculation results of the first frequency interval.

[0011] As a preferred technical solution, the process of predicting the second frequency interval is implemented by a feedforward controller.

[0012] As a preferred technical solution, the process of adjusting the second frequency interval by using a negative feedback mechanism is implemented by a PID control algorithm.

[0013] As a preferred technical solution, the parameters of the PID control algorithm include proportional gain, differential gain and integral gain.

[0014] As a preferred technical solution, the proportional gain, the differential gain and the integral gain are adjusted according to a corresponding signal-to-noise ratio, and the signal-to-noise ratio is obtained through the filtered partial discharge signal and the residual interference signal.

[0015] As a preferred technical solution, the partial discharge signal data and the interference signal data are acquired by applying a square wave electric field, and the rise time of the square wave is less than 1000ns.

[0016] As a preferred technical solution, the process of extracting the corresponding frequency spectrum features is implemented by fast Fourier transform.

[0017] According to a second aspect of the present invention, a partial discharge detection device is provided, comprising a signal acquisition and analysis unit, a digital filtering unit and a feedforward feedback adaptive control unit, for implementing the method described above.

[0018] According to a third aspect of the present invention, there is provided a storage medium having a program stored thereon, wherein the program implements the method described above when executed.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The present invention sets a reasonable first threshold value according to the spectrum difference between the PD signal and the interference signal, and obtains the first frequency interval corresponding to when the spectrum difference between the PD signal and the interference signal is greater than the first threshold value, so as to realize the first adjustment of the passband of the digital filter, that is, realize the first round of filtering of the interference signal, which can effectively improve the anti-interference ability and PD signal extraction ability in the PD detection process;

[0021] 2. The present invention inputs the first frequency interval obtained each time into the spectrum difference database, and establishes a continuous spectrum difference database by acquiring the spectrum difference data results of the PD signal and the interference signal for a long time. The spectrum difference database and the feedforward feedback adaptive control mechanism are used to predict and update the second frequency interval, and the passband of the digital filter is fine-tuned for the second time in real time to achieve a second round of filtering of the interference signal to obtain the best signal-to-noise ratio, which can further improve the effectiveness of filtering out interference signals and enhance the PD signal extraction capability under ultra-short rise time square wave electric field. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic diagram of the process of the present invention;

[0023] Figure 2 Schematic diagram of the implementation process of the method in Example 1 of the present invention;

[0024] Figure 3 This is a waveform diagram of a square wave in Embodiment 1 of the present invention;

[0025] Figure 4 is the spectrum of the PD signal and the interference signal in Embodiment 1 of the present invention;

[0026] Figure 5 Schematic diagram of the spectrum difference between the PD signal and the interference signal in Example 1 of the present invention;

[0027] Figure 6 This is a schematic diagram of a feedforward feedback adaptive control unit in Embodiment 1 of the present invention;

[0028] Figure 7 The figure is a comparison diagram of the PD signal and interference signal waveforms before and after processing in Example 1 of the present invention. DETAILED DESCRIPTION

[0029] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] The output of power electronic devices in the converter station is usually a square wave high voltage with a short rise time. The rapid change of the electric field at the rising and falling edges will cause large displacement current and electromagnetic pulse interference, which may make it difficult to distinguish between partial discharge (PD) signals and interference. Therefore, it is necessary to develop interference suppression and PD signal extraction methods that are suitable for ultra-short rise time square wave high voltage. For example, frequency domain analysis methods such as fast Fourier transform (FFT) are used to analyze the signal spectrum and extract information such as the frequency component and amplitude of the PD signal. The following embodiments are implemented based on the technical solution of the present invention, and detailed implementation methods and specific operation processes are given, but the protection scope of the present invention is not limited to the following embodiments.

[0031] Example 1

[0032] like Figure 1 As shown, this embodiment provides a partial discharge detection method, which includes the following steps:

[0033] Step S1, obtaining partial discharge signal data and interference signal data, extracting corresponding frequency spectrum features, and calculating the frequency spectrum difference between the partial discharge signal and the interference signal;

[0034] Step S2, calculating a first frequency interval when the frequency spectrum difference between the partial discharge signal and the interference signal is greater than a first threshold, filtering the signal outside the corresponding first frequency interval, and obtaining the filtered partial discharge signal and the residual interference signal, wherein the first threshold is determined by the frequency spectrum difference between the partial discharge signal and the interference signal;

[0035] Step S3, based on the filtered partial discharge signal, the residual interference signal and the spectrum difference database, predict the second frequency interval, adjust the second frequency interval by using a negative feedback mechanism, and extract the partial discharge signal under the highest signal-to-noise ratio, the spectrum difference database is preset.

[0036] like Figure 2 As shown, the PD detection method is implemented by a digital filter, a feedforward controller and a feedback adaptive controller, and the feedforward controller and the feedback adaptive controller constitute a feedforward feedback adaptive control system. The implementation process of the PD detection method is as follows:

[0037] In step S1, in order to obtain PD signal data and interference signal data, a square wave high electric field with an ultra-short voltage rise time is continuously applied to the sample. The square wave rise time used in this embodiment is 150ns, and its waveform is as follows: Figure 3As shown, using a non-contact monitoring method, a wide-band antenna sensor with a frequency band of 0.5 to 8 GHz is selected, and the data continuously acquired by the high sampling rate acquisition card include: displacement current interference at the rising and falling edges of the square wave, electromagnetic pulse interference, environmental interference, PD signal waveform data, and time domain information. After acquiring the data, the spectral characteristics of the PD signal waveform data and the interference signal data are analyzed. The displacement current interference at the rising and falling edges of the square wave, electromagnetic pulse interference, and PD signals are usually pulse signals and are non-periodic signals. The spectral characteristics of non-periodic signals are analyzed by Fourier transform. The spectrum of the non-periodic signal is a continuous spectrum, and its Fourier transform formula is:

[0038]

[0039] Among them, ω represents the signal angular frequency, F(jω) and f(t) are the frequency domain and time domain functions of the signal respectively, and t is the time variable. For pulse signals, the Gaussian function can be used as an example for analysis:

[0040]

[0041]

[0042] In equations (2) and (3), I0 represents the pulse peak current; t is the time variable; τ is the time constant; T p Represents the pulse width, and Fourier transform is performed on equation (2):

[0043]

[0044] In formula (4), f represents the signal frequency, and ω represents the signal angular frequency. Formula (4) shows that the spectrum of the pulse signal is widely distributed in the whole frequency domain. Combining formula (3) with formula (4) for monotonicity analysis, it can be seen that the pulse width T p The narrower the τ value is, the larger the high-frequency component value of the corresponding discharge pulse is. Usually, the PD pulse width is narrower than the electromagnetic interference pulse of the square wave at the voltage conversion moment, which can be distinguished by the difference in the spectrum between the two. The spectrum of a typical interference signal and a PD signal is as follows: Figure 4 (a) and Figure 4 (b) as shown.

[0045] According to formula (5), the spectrum difference between the current PD signal and the interference signal is calculated:

[0046] ΔF(jω)=F PD (jω)-F EMI (jω) (5)

[0047] Where, ΔF represents the spectrum difference between the PD signal and the interference signal, F PD Indicates the amplitude-frequency characteristics of the PD signal, F EMIIndicates the amplitude-frequency characteristics of the interference signal. Figure 4 Take 2 as an example, the spectrum difference result is as follows: Figure 5 shown.

[0048] In step S2, a first threshold is determined according to the calculated spectrum difference ΔF, and when the spectrum difference is greater than the first threshold, the corresponding first frequency interval is obtained, and the passband of the data filter is updated and adjusted according to the first frequency interval to filter the signal outside the corresponding first frequency interval, so that the information of the PD signal and the residual interference signal after the initial filtering can be obtained in the output signal. Figure 5 It can be seen that the largest frequency spectrum difference interval is 0.9-1.0 GHz. The first round of adjustment of the digital filter passband is performed according to the first frequency interval, and the first frequency interval corresponding to the frequency spectrum difference output each time is input into the spectrum difference database. By acquiring the spectrum difference data results of the PD signal and the interference signal for a long time, a continuous spectrum difference database is established. The spectrum difference database is used as the basis for determining the final digital filter passband, effectively filtering out interference and extracting partial discharge signals.

[0049] In step S3, in order to further effectively filter out the interference signal, the PD signal after the initial filtering and the residual interference signal are input into the feedforward feedback adaptive control system to automatically optimize the passband of the digital filter and output the final PD signal, such as Figure 6 As shown. Among them, r(t) is the input, y(t) is the output, and e(t) is the deviation between the predicted value and the output value in the feedforward process. The specific working process of the feedforward feedback adaptive control system is: after the spectrum difference value output each time in step S2 is input into the spectrum difference database, it is then input into the feedforward controller; the feedforward controller predicts a reasonable digital filter passband range, that is, the second frequency interval, through the spectrum difference database; the feedback adaptive controller adopts an adaptive PID (Proportion Integration Differentiation) controller. The adaptive PID controller implements a real-time second round of fine-tuning of the passband of the digital filter through a negative feedback mechanism according to the PD signal and the residual interference signal after the initial filtration, so as to obtain the best signal-to-noise ratio, and realize the suppression of interference under the high electric field of the ultra-short rise time square wave and the extraction of the PD signal. The algorithm used by the adaptive PID controller is designed as follows:

[0050]

[0051]

[0052]

[0053] in, is an adjustable parameter vector, K p , K i , Kd are proportional, differential and integral gains respectively, and ξ(e) is the regression vector. In the control process, the adaptive mechanism is constantly adjusted to obtain the optimal solution. Figure 7 As shown, a comparison of the PD signal and interference signal waveforms before and after being processed by the method provided in this embodiment is given, indicating that the method provided in this embodiment has good interference suppression capability and signal extraction capability.

[0054] Example 2

[0055] This embodiment provides a partial discharge detection device, which includes a signal acquisition and analysis unit, a digital filtering unit and a feedforward feedback adaptive control unit, and is used to implement the method in Embodiment 1.

[0056] The signal acquisition and analysis unit includes a wideband sensor, a signal amplification subunit and a high sampling rate acquisition card, which is used to acquire PD signals and interference signals, and set the spectrum analysis range according to the signal bandwidth to realize the spectrum difference operation of the PD signal and the interference signal;

[0057] The digital filtering unit includes a bandpass digital filter with a variable cutoff frequency. When the spectrum difference between the PD signal and the interference signal is greater than a first threshold, a corresponding first frequency interval is obtained, the passband of the digital filter is initially adjusted, and the signal outside the corresponding first frequency interval is filtered to obtain the filtered PD signal and the residual interference signal. The first threshold is determined by the spectrum difference between the partial discharge signal and the interference signal, and the first frequency interval obtained each time is input into a spectrum difference database. By obtaining the spectrum difference data results of the PD signal and the interference signal for a long time, a continuous spectrum difference database is established for storing and uniformly managing the spectrum difference data of the PD signal and the interference signal.

[0058] The feedforward feedback adaptive control unit includes a feedforward controller and an adaptive PID controller. The feedforward controller predicts a second frequency interval based on a database of spectrum differences between the filtered PD signal and the residual interference signal. The adaptive PID controller continuously adjusts the PID controller based on an adaptive method according to the actual frequency interval (corresponding to the case where the spectrum difference between the filtered PD signal and the residual interference signal is greater than a first threshold) and the predicted second frequency interval. The matrix parameters are used to implement a second real-time fine-tuning of the passband of the digital filter to achieve maximum suppression of displacement current interference, electromagnetic pulse interference and environmental interference signals including the rising and falling edges of the square wave, and to achieve maximum signal-to-noise ratio extraction of the PD signal.

[0059] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the unit can refer to the corresponding process in the aforementioned embodiment 1, and will not be repeated here.

[0060] Further, the present invention also provides a storage medium, on which a program is stored, and when the program is executed, the method in embodiment 1 is implemented. The program code for implementing the method can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as an independent software package and partially on a remote machine or completely on a remote machine or server. Among them, a computer-readable medium can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of machine-readable storage media would include electrical connections based on 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), optical fibers, a portable compact disk-read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0061] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A partial discharge detection method, characterized in that: The following steps are involved: S1, obtaining partial discharge signal data and interference signal data, extracting corresponding frequency spectrum features, and calculating the frequency spectrum difference between the partial discharge signal and the interference signal, wherein the partial discharge signal data and the interference signal data are obtained by applying a square wave electric field, and the rise time of the square wave is less than 1 μs; S2, calculating a first frequency interval when the frequency spectrum difference between the partial discharge signal and the interference signal is greater than a first threshold, filtering signals outside the first frequency interval, and obtaining a filtered partial discharge signal and a residual interference signal, wherein the first threshold is determined by the frequency spectrum difference between the partial discharge signal and the interference signal; S3, predicting a second frequency interval based on the filtered partial discharge signal, the residual interference signal and the spectrum difference database, and adjusting the second frequency interval by using a negative feedback mechanism to extract the partial discharge signal with the highest signal-to-noise ratio, wherein the spectrum difference database is preset; The process of predicting the second frequency interval is implemented by a feedforward controller; The process of adjusting the second frequency interval by using a negative feedback mechanism is implemented by a PID control algorithm.

2. A partial discharge detection method according to claim 1, characterized in that: The spectrum difference database is continuous, and the spectrum difference database includes calculation results of the first frequency interval.

3. A partial discharge detection method according to claim 1, characterized in that: The parameters of the PID control algorithm include proportional gain, differential gain and integral gain.

4. A partial discharge detection method according to claim 3, characterized in that: The proportional gain, the differential gain and the integral gain are adjusted according to a corresponding signal-to-noise ratio, and the signal-to-noise ratio is obtained by the filtered partial discharge signal and the residual interference signal.

5. A partial discharge detection method according to claim 1, characterized in that: The process of extracting the corresponding frequency spectrum features is achieved by fast Fourier transform.

6. A partial discharge detection device, characterized in that: The partial discharge detection device comprises a signal acquisition and analysis unit, a digital filtering unit and a feedforward feedback adaptive control unit, and is used to implement the method according to any one of claims 1 to 5.

7. A storage medium having a program stored thereon, characterized in that: When the program is executed, the method according to any one of claims 1 to 5 is implemented.

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