A partial discharge signal denoising system and method based on an improved wavelet thresholding algorithm

By using an improved wavelet thresholding algorithm, which combines spectral-constrained singular value decomposition and multi-scale wavelet decomposition with scale-correlated confidence distribution and continuous threshold field distribution, the problem of narrowband interference and white noise suppression in partial discharge signals of power equipment is solved, thereby improving the sensitivity of signal detection and the accuracy of fault identification.

CN122307276APending Publication Date: 2026-06-30HARBIN UNIV OF COMMERCE
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HARBIN UNIV OF COMMERCE
Filing Date
2026-06-01
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing technologies struggle to effectively remove narrowband interference and white noise from partial discharge signals in power equipment, resulting in low signal-to-noise ratios and affecting the accuracy of equipment condition assessments.

Method used

An improved wavelet thresholding algorithm is adopted, which combines spectral-constrained singular value decomposition and multi-scale wavelet decomposition with scale-correlated confidence distribution and continuous threshold field distribution to achieve synergistic suppression of narrowband interference and white noise, forming an iterative optimization closed-loop processing.

Benefits of technology

It significantly improves the detection sensitivity of partial discharge signals and the accuracy of fault mode identification, providing reliable equipment condition assessment data.

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Abstract

This invention relates to the field of discharge signal processing technology, specifically to a partial discharge signal denoising system and method based on an improved wavelet thresholding algorithm. The method includes: acquiring and preprocessing the original partial discharge signal from power equipment; performing singular value decomposition with spectral constraints, determining constraints based on the spectral entropy distribution, and suppressing narrowband interference; performing multi-scale wavelet decomposition; establishing a scale-related confidence distribution based on the normalized cross-correlation coefficients of adjacent scale detail coefficients; solving for the extrema of the threshold field energy functional to generate a continuous threshold field; processing the detail coefficients using a single continuous threshold function with confidence-adaptive modulation; obtaining the denoised signal through inverse wavelet transform, and iteratively correcting the confidence distribution using the processed coefficient energy distribution to form a closed loop. This invention achieves synergistic suppression of narrowband interference and white noise, significantly improving detection sensitivity, and effectively resolving the contradiction between edge preservation and noise suppression through iterative optimization of the closed loop.
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