Partial discharge signals denoising by the combination of signal decomposition and adaptive filtering
Xianhao Fan, Hanhua Luo, Fangwei Liang, Gen Chen, Chuanyang Li, Jinliang He · IET conference proceedings. · 2025
Accurate detection of partial discharge (PD) signals emitted from gas-insulated equipment is essential for identifying potential insulation faults. However, existing PD denoising methods cannot adaptively adjust model parameters based on signal characteristics, thus limiting their generalization ability and accuracy in complex noise environments. To address this limitation, this paper proposes a parameter-adaptive PD denoising strategy based on an intelligent optimization algorithm framework. The strategy involves constructing a PD denoising program that integrates signal decomposition, entropy criteria, and filtering analysis. To enhance the program's adaptability to signals with diverse characteristics, an adaptive strategy i s introduced. Simulation results demonstrate the efficacy of the proposed method in denoising composite signals with complex components.