Partial discharge detection system based on S-G filter

Abstract

The utility model discloses a partial discharge detection system based on an S-G filter, and the system comprises a signal collection module which collects a partial discharge signal; the pre-processing module is used for acquiring and pre-processing the partial discharge signal; the S-G smooth filtering module is used for carrying out smoothing and denoising processing on the preprocessed partial discharge signal; the pulse width calculation module is used for setting start and stop positions of partial discharge signals and calculating a pulse width value; and the analysis module analyzes the pulse width data and obtains a partial discharge diagnosis result. According to the utility model, the pre-processing module, the S-G smooth filtering module and the pulse width calculation module are arranged to carry out pre-processing and S-G smooth filtering processing on a partial discharge signal, the pulse width is calculated, and the type and the size of partial discharge are diagnosed according to the pulse width, so that powerful support is provided for partial discharge monitoring of power equipment; the S-G smooth filtering module can effectively suppress noise and improve the precision and reliability of signal detection.

Description

Technical Field

[0001] This utility model relates to the field of partial discharge detection technology, and in particular to a partial discharge detection system based on an SG filter. Background Technology

[0002] Partial discharge (PD) is a discharge phenomenon that occurs in localized areas of the insulation layer of high-voltage electrical equipment under the influence of a strong electric field. This phenomenon not only leads to the degradation of the insulation medium but can also cause more serious electrical faults. Therefore, effective detection and monitoring of partial discharge is crucial for the safe operation of power systems. However, the complexity of field conditions makes the detection and analysis of partial discharge signals difficult. Pulse width is the duration of a high-level signal. Traditional detection methods struggle to effectively distinguish partial discharge signals from noise signals when processing signals in complex field environments, and the accuracy and reliability of pulse width calculations are limited. Utility Model Content

[0003] The purpose of this invention is to provide a partial discharge detection system based on an SG filter to solve the problem that partial discharge detection and analysis cannot calculate pulse width accuracy.

[0004] The technical solution adopted by this utility model to solve the technical problem is as follows:

[0005] A partial discharge detection system based on an SG filter includes: a signal acquisition module for acquiring partial discharge signals; a preprocessing module for acquiring and preprocessing the partial discharge signals; an SG smoothing filter module for smoothing and denoising the preprocessed partial discharge signals; a pulse width calculation module for setting the start and end positions of the partial discharge signals and calculating the pulse width value; and an analysis module for analyzing the pulse width data and obtaining partial discharge diagnostic results.

[0006] Preferably, the SG smoothing filter module includes an SG filter for performing local polynomial fitting on the partial discharge signal to estimate the smoothing value.

[0007] Preferably, the SG filter parameters include: window width and polynomial order.

[0008] Preferably, the window width is an odd number, ranging from 85 to 100, and the polynomial order is 3.

[0009] Preferably, the window width is 99.

[0010] Preferably, the preprocessing module acquires the partial discharge signal and takes a positive value.

[0011] Preferably, the start and end positions of the partial discharge signal are set to S, and the range of S is 10%-30% of the peak value of the partial discharge signal.

[0012] Preferably, S is 10%, 15%, 20%, or 30%.

[0013] Preferably, the analysis module acquires the partial discharge type, and the partial discharge signal type includes: surface discharge, floating discharge, insulating discharge, tip discharge, and any combination thereof.

[0014] This invention preprocesses and smooths the partial discharge signal using a preprocessing module, an SG smoothing filter module, and a pulse width calculation module. The pulse width is calculated, and the partial discharge type and magnitude are diagnosed based on the pulse width, providing strong support for partial discharge monitoring of power equipment. The SG smoothing filter module effectively suppresses noise, improving the accuracy and reliability of signal detection. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the structural system connection of this utility model;

[0016] In the diagram: 1-Signal acquisition module; 2-Preprocessing module; 3-SG smoothing filter module; 4-Pulse width calculation module; 5-Analysis module. Detailed Implementation

[0017] The technical solution of this utility model will be further described below with reference to the embodiments and accompanying drawings.

[0018] A partial discharge detection system based on an SG filter includes: a signal acquisition module for acquiring partial discharge signals; a preprocessing module for acquiring and preprocessing the partial discharge signals; an SG smoothing filter module for smoothing and denoising the preprocessed partial discharge signals; a pulse width calculation module for setting the start and end positions of the partial discharge signals and calculating the pulse width value; and an analysis module for analyzing the pulse width data and obtaining partial discharge diagnostic results.

[0019] In a further embodiment of this example, the SG smoothing filter module includes an SG filter, which is used to perform local polynomial fitting on the partial discharge signal and estimate the smoothing value. After the noise in the partial discharge pulse signal is processed by the SG filter, it is effectively suppressed and the waveform trend is enhanced, thereby improving the readability of the data.

[0020] In a further implementation of this embodiment, the SG filter parameters include: window width and polynomial order; the window width determines the number of neighboring points used to fit the polynomial at each location, and a larger window width can remove noise more effectively. At the same time, the window width must be an odd number and cannot exceed the length of the partial discharge signal; the polynomial order determines the complexity of the fitting, and a higher order fits the details in the partial discharge signal better. The appropriate window width and polynomial order are selected according to the characteristics of the partial discharge signal data to achieve the best filtering effect.

[0021] In a further implementation of this embodiment, the window width is an odd number, ranging from 85 to 100, and the polynomial order is 3, which minimizes the calculation error for the pulse width, not exceeding 5%.

[0022] In a further implementation of this embodiment, setting the window width to 99 yields the best results.

[0023] In a further implementation of this embodiment, the preprocessing module acquires the partial discharge signal and takes a positive value. Since all signals are positive, it is convenient to extract all data within the peak range of the partial discharge signal.

[0024] In a further embodiment of this example, the start and end positions of the partial discharge signal are set to S, and the range of S is 10%-30% of the peak value of the partial discharge signal, which can accurately calculate the pulse width of the partial discharge signal pulse waveform.

[0025] In a further embodiment of this example, S is 10%, 15%, 20%, or 30%. In this example, S is set to 20%, and the start and end positions of the partial discharge signal are set to 20% of the peak value of the pulse waveform.

[0026] In a further implementation of this embodiment, the analysis module obtains the partial discharge type, which includes: surface discharge, floating discharge, insulating discharge, tip discharge, and any combination thereof; pulse width analysis is performed on different types of partial discharge pulses, which can effectively identify the pulse width of different types of partial discharge, thereby distinguishing the type and size of partial discharge and effectively diagnosing the on-site power equipment.

[0027] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this utility model, and not to limit it. Although this utility model has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this utility model.

Claims

1. A partial discharge detection system based on an SG filter, characterized in that, include: The signal acquisition module acquires partial discharge signals; the preprocessing module acquires and preprocesses the partial discharge signals. The SG smoothing filter module smooths and denoises the preprocessed partial discharge signal; the pulse width calculation module sets the start and end positions of the partial discharge signal and calculates the pulse width value; the analysis module analyzes the pulse width data and obtains the partial discharge diagnosis results.

2. The partial discharge detection system based on an SG filter according to claim 1, characterized in that, The SG smoothing filter module includes an SG filter, which is used to perform local polynomial fitting on the partial discharge signal and estimate the smoothing value.

3. The partial discharge detection system based on an SG filter according to claim 1, characterized in that, The SG filter parameters include: window width and polynomial order.

4. The partial discharge detection system based on an SG filter according to claim 3, characterized in that, The window width is an odd number, ranging from 85 to 100, and the polynomial order is 3.

5. The partial discharge detection system based on an SG filter according to claim 4, characterized in that, The window width is 99.

6. The partial discharge detection system based on an SG filter according to claim 1, characterized in that, The preprocessing module acquires the partial discharge signal and takes a positive value.

7. The partial discharge detection system based on an SG filter according to claim 1, characterized in that, The start and end positions of the partial discharge signal are set to S, and the range of S is 10%-30% of the peak value of the partial discharge signal.

8. The partial discharge detection system based on an SG filter according to claim 7, characterized in that, The value of S is 10%, 15%, 20%, or 30%.

9. The partial discharge detection system based on an SG filter according to claim 1, characterized in that, The analysis module acquires the partial discharge type, which includes: surface discharge, floating discharge, insulating discharge, tip discharge, and any combination thereof.

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