Partial discharge(PD)is a critical indicator of the operational status of switchgear cabinets.However,the partial discharge signals collected on-site are often obscured by periodic narrowband interference and Gaussian white noise.To accurately analyze these signals and ensure the safety and reliability of switchgear,a denoising method combining Ensemble Empirical Mode Decomposition(EEMD)and wavelet thresholding is proposed.Initially,noisy partial discharge signals undergo EEMD decomposition.The Intrinsic Mode Functions(IMFs)are then subjected to threshold evaluation using correlation coefficients to eliminate spurious components.Subsequent wavelet threshold processing is applied to the retained IMFs.Finally,the IMFs are reconstructed to obtain a useful partial discharge signal.Test results demonstrate that this method effectively removes noise while preserving the characteristics of partial discharge,enhancing the interpretability and reliability of the analysis.
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