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Partial discharge (PD) is key to assessing transformer insulation, but traditional SVD struggles to effectively suppress white noise, often leaving residual noise and losing signal details. To address this, a denoising algorithm combining SVD with PSO-optimized VMD is proposed. First, SVD removes narrowband interference by zeroing specific singular values. Then, PSO optimizes VMD parameters for better decomposition. The resulting IMFs are denoised and reconstructed to suppress white noise. When the initial SNR is −28.594 dB, the method boosts it to 16.696 dB, outperforming traditional techniques in handling both white noise and narrowband interference.

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Noise Suppression Method for Partial Discharge Signals Based on SVD and PSO-Optimized VMD

  • 会议论文

  • 发表日期：

    2026年

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  • Xiangzhi Fan,
  • Xin Zhang,
  • Bo Liu,
  • Yongji Guo,
  • Chaoming Zhang,
  • Hai Jin

摘要

Partial discharge (PD) is key to assessing transformer insulation, but traditional SVD struggles to effectively suppress white noise, often leaving residual noise and losing signal details. To address this, a denoising algorithm combining SVD with PSO-optimized VMD is proposed. First, SVD removes narrowband interference by zeroing specific singular values. Then, PSO optimizes VMD parameters for better decomposition. The resulting IMFs are denoised and reconstructed to suppress white noise. When the initial SNR is −28.594 dB, the method boosts it to 16.696 dB, outperforming traditional techniques in handling both white noise and narrowband interference.