A discharge current peak time instant inversion method based on electromagnetic wave signals

Abstract

The application discloses a discharge current peak moment inversion method based on an electromagnetic wave signal and relates to the field of pulse current characteristic inversion, and the method comprises the following steps: S1, obtaining an external environment state and analyzing to obtain environment parameters, combining the environment parameters and GIS device parameters to construct a partial discharge simulation model; S2, obtaining electromagnetic wave signals generated by past partial discharges and excitation source parameters, analyzing the electromagnetic wave signals to obtain characteristic parameters, combining the characteristic parameters and the excitation source parameters to construct a partial discharge excitation source model in the partial discharge simulation model; S3, obtaining a current demand setting excitation source and a probe, simulating the propagation and response of the partial discharge in the GIS interior in the partial discharge excitation source model and recording a voltage signal waveform; and S4, combining the voltage signal waveform to obtain a peak moment according to a time inversion algorithm, wherein the peak waveform obtained by the application is more accurate than the waveform collected by a monitoring device, and the positioning accuracy of a discharge source is further improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of pulse current characteristic inversion, and in particular to a discharge current peak time inversion method based on electromagnetic wave signals. BACKGROUND

[0002] The strong uncertainty, volatility and large amount of harmonics introduced by the new power system will cause the power equipment to bear more extreme and drastic changes in operating conditions, and higher requirements for the safe and reliable operation of the power equipment. Comprehensive, timely and accurate perception of the state of power equipment is a prerequisite for ensuring the safety of the equipment, and is also a technical bottleneck for realizing the digitization and intelligentization of power equipment.

[0003] The digitization and intelligentization of GIS equipment under the current new power system background are still in the initial stage, and the existing GIS state monitoring technology cannot comprehensively and accurately grasp the internal state of the GIS equipment. The operation and maintenance efficiency of the equipment is difficult to effectively improve, and GIS equipment failures occur from time to time. Therefore, it is necessary to carry out research on GIS equipment holographic perception and accurate evaluation technology based on multi-parameter cooperation.

[0004] Inversion of more partial discharge information is of great significance for monitoring and diagnosis of partial discharge. The peak time of pulse current is one of the important information about partial discharge. By inverting the peak time of the internal discharge signal of the equipment, a more accurate peak time than the sensor measuring the peak time outside the equipment can be obtained, thereby improving the accuracy of the discharge source positioning method based on time difference method.

[0005] Therefore, an effective discharge current peak time inversion method based on electromagnetic wave signals is urgently needed. SUMMARY

[0006] To solve the above problems, the present application provides a discharge current peak time inversion method based on electromagnetic wave signals, which further analyzes the pulse current characteristics through the pulse current peak to achieve the effect of fault prediction.

[0007] In the present application, a discharge current peak time inversion method based on electromagnetic wave signals is provided, comprising the following steps:

[0008] S1, obtaining the external environment state, analyzing the external environment state to obtain the environment parameter, and combining the environment parameter and the GIS equipment parameter to construct a partial discharge simulation model;

[0009] S2, obtaining the electromagnetic wave signal generated by the past partial discharge and the excitation source parameter, analyzing the electromagnetic wave signal to obtain the characteristic parameter, and combining the characteristic parameter and the excitation source parameter to construct a partial discharge excitation source model in the partial discharge simulation model;

[0010] S3, obtaining current demand, setting incentive source and probe according to current demand, simulating propagation and response of partial discharge in GIS interior in partial discharge incentive source model and recording voltage signal waveform;

[0011] S4, obtaining peak time according to time reversal algorithm combining voltage signal waveform, obtaining time difference between pulse current peak value and timing start time and positioning discharge source.

[0012] Preferably, the specific content of constructing the partial discharge simulation model in S1 in combination with the environmental parameters and the equipment parameters is:

[0013] The environmental parameters include: environmental temperature, environmental pressure, environmental humidity;

[0014] Obtaining GIS equipment parameters, analyzing the GIS equipment parameters to obtain structure parameters and influence parameters;

[0015] Generating a three-dimensional simulation module for the GIS equipment according to the structure parameters;

[0016] Configuring the three-dimensional simulation module according to the influence parameters;

[0017] The influence parameters include characteristic parameters of insulating materials in different structures, dielectric constant, magnetic permeability parameters, air ionization characteristic parameters and breakdown strength parameters;

[0018] The structure parameters include GIS equipment type, discharge gap distance and gap shape;

[0019] Obtaining sensor parameters and setting sensors in the three-dimensional simulation module, the sensor parameters including position parameters, sensitivity parameters, bandwidth parameters and directionality parameters.

[0020] Preferably, the specific content of obtaining the characteristic parameters by analyzing the electromagnetic wave signals in S2 is:

[0021] Performing denoising, filtering and normalization processing on the electromagnetic wave signals to improve the quality of the signals to obtain high-quality signals;

[0022] Converting the high-quality signals to the frequency domain by using the fast Fourier transform (FFT) method to analyze the frequency thereof;

[0023] Extracting the peak time, frequency component and amplitude of the high-quality signals to obtain the characteristic parameters.

[0024] Preferably, the specific content of constructing the partial discharge incentive source model in the partial discharge simulation model in S2 in combination with the characteristic parameters and the incentive source parameters is:

[0025] The incentive source parameters include incentive source type and incentive source position, and the position is calibrated in the partial discharge simulation model according to the incentive source position.

[0026] The correspondence between the excitation source type and characteristic parameters is obtained, and a double exponential decay function is selected based on the correspondence to construct a partial discharge excitation source model.

[0027] Preferably, the specific contents of simulating the propagation and response of partial discharge inside the GIS and recording the voltage signal waveform in the partial discharge excitation source model are:

[0028] Set the parameters of the current excitation source and probe. Start timing when the excitation source radiates electromagnetic waves and record the voltage signal waveform received by the probe. ;

[0029] Exchange the positions of the excitation source and the probe, reverse the received voltage signal waveform in the time domain, use it as the waveform of the excitation source, perform the simulation experiment again, and record the voltage waveform received by the probe at this time .

[0030] Preferably, the specific contents of obtaining the peak moment and the time difference between the pulse current peak and the timing start moment in combination with the voltage signal waveform according to the time reversal algorithm and then locating the discharge source are as follows:

[0031] Convolution ;

[0032] Voltage waveform and Compare the waveforms of

[0033] Calculate voltage waveform and The difference in the peak moments is the time difference between the peak moment of the pulse current and the timing start moment;

[0034] The discharge source is located according to the time difference between the peak value of the pulse current and the start time of timing combined with the time difference positioning method.

[0035] In summary, the present invention's method for inverting the discharge current peak moment based on electromagnetic wave signals, compared to traditional pulse current characteristic inversion technology, establishes a local discharge excitation source model, simulates the propagation and response of local discharge within the GIS, and records the voltage signal waveform. The voltage signal waveform is then inverted to obtain the peak moment and the time difference between the pulse current peak and the timing start moment, thereby locating the discharge source. This method is more accurate than the waveform collected by the monitoring device, thus helping to obtain a more precise arrival time difference and improving the accuracy of locating the discharge source.

[0036] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A Gaussian waveform excitation source waveform for the discharge current peak time inversion method based on an electromagnetic wave signal of the application;

[0038] Figure 2 A received signal inversion waveform under Gaussian pulse excitation for the discharge current peak time inversion method based on an electromagnetic wave signal of the application;

[0039] Figure 3 The time inversion received waveform and the convolution of the original received signal for the discharge current peak time inversion method based on an electromagnetic wave signal of the application. DETAILED DESCRIPTION

[0040] The technical solutions of the application are further described below by means of the drawings and examples. It should be noted that, unless otherwise specified, the relative arrangement, numerical expressions and values of the components and steps set forth in these examples do not limit the scope of the application.

[0041] The following description of at least one example embodiment is merely illustrative in nature and is in no way limiting to the scope of the application or its applications or uses.

[0042] Techniques, systems, and devices known to those of ordinary skill in the relevant art can not be discussed in detail herein, but should be considered part of the specification.

[0043] In all examples shown and discussed herein, any specific values should be interpreted as merely illustrative and not as a limitation. Thus, other examples of example embodiments can have different values.

[0044] Unless otherwise defined, technical or scientific terms used in the application should be interpreted as having the ordinary meaning that would be understood by a person of ordinary skill in the art to which the application belongs.

[0045] The application provides a discharge current peak time inversion method based on an electromagnetic wave signal, specifically as follows:

[0046] S1, obtaining an external environment state, analyzing the external environment state to obtain an environment parameter, and combining the environment parameter and a GIS device parameter to construct a partial discharge simulation model;

[0047] Preferably, the specific content of constructing the partial discharge simulation model in S1 by combining the environment parameter and the device parameter is:

[0048] The environment parameter is set, and the environment parameter includes: environment temperature, environment pressure, and environment humidity;

[0049] Obtaining GIS device parameters, analyzing the GIS device parameters to obtain structure parameters and influence parameters;

[0050] Generating a three-dimensional simulation module for the GIS device according to the structure parameters;

[0051] Configuring the three-dimensional simulation module according to the influence parameters;

[0052] The influence parameters include characteristic parameters of insulation materials in different structures, dielectric constant, magnetic permeability parameters, air ionization characteristic parameters, and breakdown strength parameters;

[0053] The structure parameters include GIS device types, discharge gap distances, and gap shapes;

[0054] Obtaining sensor parameters and setting sensors in the three-dimensional simulation module, the sensor parameters including position parameters, sensitivity parameters, bandwidth parameters, and directionality parameters.

[0055] S2, obtaining electromagnetic wave signals generated by past partial discharges and excitation source parameters, analyzing the electromagnetic wave signals to obtain characteristic parameters, and constructing a partial discharge excitation source model in a partial discharge simulation model by combining the characteristic parameters and the excitation source parameters;

[0056] Preferably, the specific content of analyzing the electromagnetic wave signals to obtain characteristic parameters in S2 is:

[0057] Denoising, filtering, and normalizing the electromagnetic wave signals to improve the quality of the signals to obtain high-quality signals;

[0058] Converting the high-quality signals to the frequency domain using the fast Fourier transform (FFT) method to analyze the frequency of the signals;

[0059] Extracting the peak time, frequency component, and amplitude of the high-quality signals to obtain the characteristic parameters.

[0060] Preferably, the specific content of constructing a partial discharge excitation source model in a partial discharge simulation model by combining the characteristic parameters and the excitation source parameters in S2 is:

[0061] The excitation source parameters include excitation source types and excitation source positions, and the excitation source positions are calibrated in the partial discharge simulation model;

[0062] Obtaining the corresponding relationship between the excitation source types and the characteristic parameters, and selecting a double exponential decay function to construct the partial discharge excitation source model by combining the corresponding relationship.

[0063] S3, obtaining current needs, setting excitation sources and four probes according to the current needs, simulating the propagation and response of partial discharges in GIS interiors in the partial discharge excitation source model, and recording voltage signal waveforms;

[0064] Preferably, the specific content of simulating the propagation and response of partial discharge inside GIS in the partial discharge excitation source model and recording the voltage signal waveform is as follows:

[0065] Setting the parameters of the current excitation source and probe, starting timing when the excitation source radiates electromagnetic waves outward, and recording the voltage signal waveform received by the probe ;

[0066] Swapping the positions of the excitation source and the probe, inverting the received voltage signal waveform in the time domain as the waveform of the excitation source, and performing simulation experiments again to record the voltage waveform received by the probe at this time .

[0067] The partial discharge model in the air domain is provided with an origin position and a standard grid, a dipole antenna with a length of the size of the standard grid is placed at the origin as a radiation source, and another dipole antenna with the same shape is placed at a distance of 40 cm from the origin as a receiving antenna. A non-delayed Gaussian pulse is used as the waveform of the excitation source as shown in Figure 1 . Figure 1 The waveform of the Gaussian waveform excitation source is shown in Figure 2 .

[0068] S4, combining the voltage signal waveform, obtaining the peak time according to the time reversal algorithm, and obtaining the time difference between the peak value of the pulse current and the starting time of timing to further locate the discharge source.

[0069] Preferably, the specific content of combining the voltage signal waveform, obtaining the peak time according to the time reversal algorithm, and obtaining the time difference between the peak value of the pulse current and the starting time of timing to further locate the discharge source is as follows:

[0070] Convolution obtains ;

[0071] The voltage waveform is compared with the waveform of ;

[0072] The difference between the peak time of the voltage waveform and is calculated, and the difference between the peak time is the time difference between the peak value of the pulse current and the starting time of timing;

[0073] According to the time difference between the peak value of the pulse current and the starting time of timing, the discharge source is located by the time difference positioning method. The specific positioning method is to calculate the position of the discharge source by the time difference and the propagation speed of electromagnetic waves combined with the position of the sensor.

[0074] After the position of the excitation source and the antenna is reversed, the reversed signal is smoothed and input as the excitation waveform, and the comparison result of the signal received at the original excitation source and the convolution of itself is obtained as shown in FIG. 8, wherein the red waveform is the signal received after time reversal, and the blue waveform is the result of convolution of the original received signal. Figure 3

[0075] It can be found that the time difference of the peak-to-peak time of the two is 0.11055us, the peak time of the pulse current is 0.0100143us, and the error of the two is about 0.01%. In addition, the waveforms of the two are similar, which verifies that the essence of the time reversal method after time reversal and then emission at the antenna in the time domain is to do the conjugate transformation in the frequency domain. Whether it is a symmetrical Gaussian pulse waveform or a simulated partial discharge waveform more similar to the actual pulse discharge, the time reversal method can accurately obtain the peak time of the pulse current.

[0076] Table 1 is the actual value and the estimated value of the peak time of the excitation source under air condition, and it can be found that the error of the actual value and the estimated value under the two conditions is very small, both less than 1%, which shows that the method of estimating the peak time of the pulse current based on the time reversal method is effective.

[0077] Table 1

[0078]

[0079] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application but not to limit it, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that: it can still modify or equivalently replace the technical solutions of the present application, and these modifications or equivalent replacements also cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.​

Claims

1. A method for inverting the peak moment of discharge current based on electromagnetic wave signals, characterized in that: The following steps are involved: S1. Obtain the external environmental state, analyze the external environmental state to obtain environmental parameters, and build a partial discharge simulation model by combining the environmental parameters and GIS equipment parameters; S2. Acquire electromagnetic wave signals and excitation source parameters generated by past partial discharges, analyze the electromagnetic wave signals to obtain characteristic parameters, and construct a partial discharge excitation source model in the partial discharge simulation model by combining the characteristic parameters and the excitation source parameters; S3. Obtain current demand, set the excitation source and probe according to the current demand, simulate the propagation and response of partial discharge inside the GIS in the partial discharge excitation source model, and record the voltage signal waveform; S4. Combine the voltage signal waveform and obtain the peak moment according to the time reversal algorithm, and obtain the time difference between the pulse current peak and the timing start moment, and then locate the discharge source; The specific content of the characteristic parameters obtained by analyzing the electromagnetic wave signal in S2 is: De-noising, filtering and normalization are performed on electromagnetic wave signals to improve the quality of the signals and obtain high-quality signals; Use the Fast Fourier Transform (FFT) method to convert high-quality signals into the frequency domain to analyze their frequencies; Extract the peak time, frequency component, and amplitude of high-quality signals to obtain characteristic parameters; The specific contents of constructing the partial discharge excitation source model in the partial discharge simulation model by combining the characteristic parameters and the excitation source parameters in S2 are as follows: The excitation source parameters include the excitation source type and the excitation source position, and the position calibration is performed in the partial discharge simulation model according to the excitation source position; Obtain the correspondence between the excitation source type and characteristic parameters, and select a double exponential decay function based on the correspondence to construct a partial discharge excitation source model; The specific contents of simulating the propagation and response of partial discharge inside the GIS and recording the voltage signal waveform in the partial discharge excitation source model are as follows: Set the parameters of the current excitation source and probe. Start timing when the excitation source radiates electromagnetic waves and record the voltage signal waveform received by the probe. ; Exchange the positions of the excitation source and the probe, reverse the received voltage signal waveform in the time domain, use it as the waveform of the excitation source, perform the simulation experiment again, and record the voltage waveform received by the probe at this time ; Combined with the voltage signal waveform, the peak moment is obtained according to the time reversal algorithm, and the time difference between the pulse current peak and the timing start moment is obtained. The specific contents of locating the discharge source are as follows: Convolution ; Voltage waveform and Compare the waveforms of Calculate voltage waveform and The difference in the peak moments is the time difference between the peak moment of the pulse current and the timing start moment; The discharge source is located according to the time difference between the peak value of the pulse current and the start time of timing combined with the time difference positioning method.

2. The method for inverting the peak moment of discharge current based on electromagnetic wave signals according to claim 1, characterized in that: The specific contents of building the partial discharge simulation model by combining environmental parameters and equipment parameters in S1 are as follows: Setting environmental parameters, including ambient temperature, ambient pressure, and ambient humidity; Obtain GIS equipment parameters, analyze them to obtain structural parameters and influencing parameters; Generate a three-dimensional simulation module for GIS equipment based on structural parameters; Configure the stereo simulation module according to the influencing parameters; The influencing parameters include characteristic parameters of insulating materials in different structures, dielectric constant, magnetic permeability parameters, air ionization characteristic parameters and breakdown strength parameters: The structural parameters include GIS equipment type, discharge gap distance and gap shape; The sensor parameters are obtained and set in the stereo simulation module, wherein the sensor parameters include position parameters, sensitivity parameters, bandwidth parameters, and directionality parameters.

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