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Partial discharge signal denoising method based on lifting wavelet transform

A technology of discharge signal and wavelet transformation, which is applied in the direction of testing dielectric strength, etc., can solve the problem of medium voltage cable partial discharge signal containing noise, etc., and achieve the effect of excellent denoising effect, fast denoising speed and simple calculation

Inactive Publication Date: 2014-03-12
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0003] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, provide a partial discharge signal denoising method based on lifting wavelet transform, and solve the problem that the medium voltage cable partial discharge signal contains noise

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  • Partial discharge signal denoising method based on lifting wavelet transform
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  • Partial discharge signal denoising method based on lifting wavelet transform

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Embodiment

[0040] The realization process of the present invention can be briefly summarized as:

[0041] 1. Determine the lifting scheme, the present invention is the lifting scheme of db8 wavelet, and add the lifting step ELS to the lifting scheme.

[0042] 2. Select the number of layers for lifting wavelet decomposition. In the present invention, the number of decomposition layers is N=4.

[0043] 3. Using the selected lifting scheme and the number of decomposition layers to perform lifting wavelet transform on the noisy partial discharge signal, and obtain high-frequency coefficient components of different decomposition scales and low-frequency coefficient components of the highest scale.

[0044] 4. Using layered threshold and soft threshold function based on wavelet entropy, quantize the high-frequency coefficient components obtained in step 3 to remove noise components, and save them as new high-frequency coefficient components.

[0045] 5. Use the thresholded new high-frequency ...

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Abstract

The invention relates to a partial discharge signal denoising method based on lifting wavelet transform, which includes the following steps: (1) a partial discharge signal to be denoised is inputted; (2) lifting wavelet decomposition is carried out on the partial discharge signal, so that high-frequency coefficient components of different decomposition scales and a low-frequency coefficient component of the highest scale are obtained; (3) wavelet entropy-based layered thresholds and a soft threshold function are adopted to quantify the high-frequency coefficient components in order to remove noise components, and the high-frequency coefficient components are stored as new high-frequency coefficient components; (4) the new high-frequency coefficient components and the low-frequency coefficient component of the highest scale obtained in step (3) are utilized to compose a coefficient component for signal reconstruction, signal reconstruction is carried out on the coefficient, and thereby a denoised partial discharge signal is obtained. Lifting wavelets are completely transformed in a time (space) domain, and high-pass and low-pass filters are turned into a series of relatively simple prediction and update steps. Therefore the denoising speed of lifting wavelet transform is high, the design is flexible and simple, and the partial discharge signal denoising method is easy to put into practice.

Description

technical field [0001] The invention relates to the field of signal processing and online monitoring, in particular to a partial discharge signal denoising method based on lifting wavelet transform. Background technique [0002] On-line detection of partial discharge has become an effective method to evaluate the insulation state of electrical equipment. In the online detection, the electrical equipment is in the live running state, and the on-site interference is serious; the PD signal generated by the insulation defect is usually very weak, and it is easy to be submerged in the serious background noise. Therefore, the suppression of interference is a key issue in the on-line detection of insulated PDs. According to the general order of suppressing interference, interference in PD online detection can generally be divided into three categories: periodic narrow-band interference, white noise and random pulse interference. Before suppressing random pulse interference, it is...

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Application Information

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IPC IPC(8): G01R31/12
Inventor 吴炬卓牛海清徐涛
Owner SOUTH CHINA UNIV OF TECH
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