Fault Diagnosis Feature Extraction of Marine Rolling Bearing Based on MEMD and Pe

Cui, J.-C. and Ma, L.-J., 2019. Fault diagnosis feature extraction of marine rolling bearing based on MEMD and pe. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 342–346. Coconut Creek (Florida), ISSN 0749-0208.Aiming at the modal aliasing problem of EMD method, an improved MEMD algorithm is proposed, which can greatly improve the signal-to-noise ratio of reconstructed signal and improve the modal aliasing problem. Through simulation signal analysis, the performance of MEMD method with added and subtracted noise is found. Compared with the meme and noise-added MEMD and pe methods, the optimal range of the added noise and the variance of the signal to be decomposed and the optimal number of concentrated averages are found. The signal-to-noise ratio of the reconstructed signal is continuously increased until the maximum value is applied to the gear and bearing. The analysis of the measured vibration signal of the fault shows the effectiveness of the method. The frequency of the fault feature can be clearly found from the instantaneous energy density spectrum.