Vibration signal denoising of switch machines based on CPO-VMD-SWTTV method
YANG Hangtao
FENG Qingsheng
HAN Zhun
XIAO Shuai
SONG Yakun
LIANG Tiantian
Abstract：To address the challenge of extracting fault features from switch machine vibration signals under varying noise conditions,this study proposes a denoising method combining Crested Porcupine Optimization(CPO)-optimized Variational Mode Decomposition(VMD)with Stationary Wavelet Transform Total Variation(SWTTV).First,the vibration signal is decomposed into multiple Intrinsic Mode Functions(IMF)using CPO-optimized VMD.Second,a hybrid criterion combining correlation coefficient and kurtosis is employed to select relevant IMFs.The selected IMFs are then denoised and reconstructed using the SWTTV algorithm.Finally,the method's performance is evaluated using both simulated test signals and field-collected switch machine vibration signals.Experimental results demonstrate that under different Signal Noise Ratios(SNR),compared to the VMD-WT algorithm,the proposed method achieves an improvement in output SNR of approximately 1 to 6 dB,a reduction in Root Mean Square Error(RMSE)by about 0.03,and an increase in the correlation coefficient with the original signal by approximately 0.01.Furthermore,the proposed algorithm effectively preserves signal features under various operating conditions,avoiding signal distortion.The proposed algorithm exhibits strong generalization capability and robustness,providing a theoretical basis for feature extrac-tion and fault diagnosis of switch machine vibration signals.
Keywords：switch machinevibration signal denoisingCrested Porcupine Optimization(CPO)Variational Mode Decomposition(VMD)Stationary Wavelet Transform Total Variation(SWTTV)
Publication Date：2025-12-30
Online Publishing Date：2026-02-02(First online date of this platform, not the publication date of the document)
Pages：14( 41-54 )