The Denoising Method of OLTC Vibration Signals Based on Ensemble Empirical Mode Decomposition and Wavelet Thresholding

In view of the characteristics of nonlinearity, non-stationarity, and strong noise in the mechanical fault signals of on-load tap changer (OLTC), the traditional empirical mode decomposition (EMD) suffers from problems such as mode mixing and spurious modes. Therefore, this paper proposes a denoising method for OLTC vibration signals based on integrated empirical mode decomposition and wavelet thresholding. Firstly, the vibration signal is decomposed into modes using ensemble empirical mode decomposition (EEMD). Then, wavelet thresholding is applied to each decomposed mode for denoising. The denoised modes are then reconstructed to achieve signal denoising. The effectiveness of the proposed method is verified by comparing it with the EMD decomposition. Experimental results demonstrate that the proposed method performs well in denoising OLTC vibration signals. The signal-to-noise ratio, root mean square error, and waveform similarity parameters are superior to those achieved by the EMD decomposition method, significantly improving the denoising effect of OLTC vibration signals and laying a foundation for subsequent research on OLTC condition monitoring and fault diagnosis.