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A New Method for Partial Discharge Signal Processing

A partial discharge (PD) signal processing method based on dynamic measurement theory and wavelet transform is proposed in this paper. The deterministic component was separated by polynomial fitting, and the random component of the remaining residual after the separation was estimated using autoregressive (AR) model; The true value estimate and dynamic measurement uncertainty of noisy signal were obtained by the deterministic component and random component;Db8 wavelet and the soft threshold based on Stein’s Unbiased Estimate of Risk were used to smoothly denoise for better PD signal processing. Finally, the effectiveness of the method was verified by MATLAB simulation and experimental noisy PD signal extraction.