Typical electrode discharge acoustic signal denoising in oil based on improved VMD

Abstract

In order to suppress the white noise interference in partial discharge (PD) detection and accurately extract the characteristics of local discharge pulse acoustic signal of transformer under strong noise environment, the adaptive separation and denoising of the discharge pulse acoustic signal were analyzed under low signal-to-noise ratio (SNR) environment. Firstly, the optimal decomposition mode number K of the variational mode decomposition (VMD) was determined based on Spearman correlation coefficient, then the reliability of the proposed Spearman-variational mode decomposition (SVMD) method decomposition was verified by simulated signals, and finally the actual discharge pulse acoustic signal was decomposed and denoised based on the Spearman correlation coefficient averaging threshold method to extract the eigenmode function components of the discharge pulse signal. The results showed that SVMD adaptively solved the unknown defects of VMD mode number, and effectively extracted the modal components of complex signals, and successfully realized the denoising of transformer partial discharge acoustic signals. The proposed method effectively removed white noise interference in the partial discharge acoustic signal and obtained a smooth filtered signal. It retained the integrity of the partial discharge signal to the maximum extent and was beneficial to the subsequent research of partial discharge. The improvement of VMD was helpful to promote its wide use in industrial equipment condition inspection.

Keywords

failure recognition / Spearman correlation coefficient / variational mode decomposition(VMD) / partial discharge / acoustic signal

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