A multi-element power load access network wave signal extraction adaptive noise reduction method

By combining time-domain peak factor and frequency-domain three-segment bandpass filter with improved Wiener filtering, dynamic notch filtering and normalized LMS algorithm, accurate classification and adaptive suppression of traveling wave signals in distribution networks with diversified power supply loads are achieved. This solves the problems of incomplete noise suppression and poor adaptability in existing technologies, and improves signal extraction accuracy and robustness.

CN122241000APending Publication Date: 2026-06-19XIANGYANG POWER SUPPLY COMPANY OF STATE GRID HUBEI ELECTRIC POWER
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
XIANGYANG POWER SUPPLY COMPANY OF STATE GRID HUBEI ELECTRIC POWER
Filing Date
2026-03-12
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

Existing technologies suffer from low accuracy and poor adaptability in extracting traveling wave signals after diverse power loads are connected to the distribution network. They cannot effectively suppress switching noise, pulse noise, and narrowband interference, and the parameter configuration is complex, making it difficult to meet the needs of fault location and condition monitoring.

Method used

Noise intelligent classification is achieved by using time-domain peak factor and frequency-domain three-segment bandpass filter. Combined with improved Wiener filtering algorithm, dynamic notch filtering and normalized LMS algorithm, adaptive suppression of switching noise, impulse noise and narrowband interference is realized. Signal quality is ensured by verifying the signal-to-noise ratio and traveling wave correlation.

Benefits of technology

It improves the accuracy and robustness of traveling wave signal extraction, adapts to the dynamic operating conditions of diverse power loads, reduces the difficulty of engineering implementation, and enhances the signal-to-noise ratio and noise suppression effect.

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Abstract

This invention relates to the field of distribution network signal processing, and provides an adaptive noise reduction method for extracting traveling wave signals from distribution networks with diverse power loads. The method includes: acquiring the traveling wave current signal from the distribution network; determining the time-domain pulse intensity using a peak factor; performing bandpass filtering energy detection to achieve intelligent noise classification; employing an improved Wiener filtering algorithm based on sliding window covariance estimation to process the switching noise of the signal; employing a dynamic notch filtering method combining spectral peak tracking and simplified first-order filtering to process the pulse noise of the signal; optimizing the weight coefficient update logic through real-time normalization of input power step size to suppress narrowband interference; verifying the quality of the noise-reduced signal from both signal-to-noise ratio and traveling wave correlation aspects, and extracting and outputting the traveling wave signal. This invention achieves accurate classification and targeted adaptive suppression of three types of high-frequency noise, improving the accuracy and robustness of traveling wave signal extraction, and adapting to the dynamic operating conditions of the distribution network.
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