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Denoising of partial discharge signals based on adaptive singular value decomposition and discrete wavelet transform | Synapse
March 3, 2026
Denoising of partial discharge signals based on adaptive singular value decomposition and discrete wavelet transform
YZ
Yun Zhao
Northwest Normal University
HL
Hong Liu
RT
Rui Tang
Army Medical University
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Key Points
Effective denoising of partial discharge signals enhances detection accuracy, and improves reliability in monitoring systems.
Signal processing techniques like adaptive singular value decomposition combined with discrete wavelet transform are employed.
Assessment using simulation models indicates up to 30% reduction in noise levels, enhancing the clarity of signals.
May enable more accurate diagnostics in electrical equipment to prevent potential failures and improve safety.
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Zhao et al. (Tue,) studied this question.
synapsesocial.com/papers/69a76088c6e9836116a2d5e9
https://doi.org/https://doi.org/10.1007/s43236-026-01286-4
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