Denoising of rolling bearing vibration signals based on CEEMDAN-IAWT method

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (13) : 199-207.

REN Haijun, WEI Chong, TAN Zhiqiang, LUO Liang, DING Xianfei

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Abstract

To solve the problem of mixing noise into rolling bearing vibration signals, a joint noise reduction method is designed, which combines the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the improved adaptive wavelet threshold (IAWT). First, use CEEMDAN to modal decomposition of the signal to obtain intrinsic mode functions (IMFs); Then the obtained IMFs and the original signal were analyzed to identify the effective component. Aiming at the problem that wavelet threshold denoising algorithm(WT) can not adaptively select wavelet base and decomposition layer and threshold function has defects, IAWT algorithm is designed, IAWT algorithm is used to filter noise in IMFs. Finally, the processed IMFs signal is reconstructed. The designed joint denoising algorithm is used to process simulation signals and experimental signals. Compared with WT, the signal-to-noise ratio of the signal processed by IAWT is improved by about 0.5dB, the correlation coefficient with the original signal is increased by about 0.03, and the root mean square error is reduced by about 0.01. By comparing the proposed method with CEEMDAN-WT and other methods, the signal-to-noise ratio of signal processed by the proposed method is improved by at least 1.37dB, and the signal characteristics are well preserved.

Key words

rolling bearing / vibration signal noise reduction / complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) / improved adaptive wavelet threshold(IAWT);

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REN Haijun, WEI Chong, TAN Zhiqiang, LUO Liang, DING Xianfei. Denoising of rolling bearing vibration signals based on CEEMDAN-IAWT method[J]. Journal of Vibration and Shock, 2023, 42(13): 199-207

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