Study on vibration mode of remanufactured engine based on EEMD

Abstract

In order to extract the vibration feature of remanufactured engines, the vibration signal is decomposed by ensemble empirical mode decomposition(EEMD), and this method is applied to study vibration mode of remanufactured engines. Based on the decomposition of vibration signal, correlation coefficient is introduced to study the correlation between IMF(Intrinsic Mode Function) components and original signal, and sensitive factors of IMF components are calculated using correlation coefficients. Hilbert transform is made with sensitive IMF components. The study results show that vibration feature of remanufactured engines is include in IMF components decomposed by EEMD, the vibration modes of remanufactured engines can be differentiated by Hilbert-Huang spectrum and marginal spectrum based on sensitive IMF components. According to vibration feature, the vibration state of remanufactured engines is divided into cylinder wall, cylinder cover and crankshaft vibration modes, which are important to improve the remanufacture level of engines.

A hybrid intelligent gearbox fault diagnosis method based on EWCEEMD and whale optimization algorithm-optimized SVM

“…The IMF that stores large amount of fault information is defined as sensitive IMF, while the IMF that stores correspondingly weak fault information is defined as non-sensitive IMF. Chen et al (2014) calculated the sensitivity of IMF by correlation coefficient method to extract the vibration characteristics of remanufactured engine. Su et al (2022) realized accurate selection of sensitive IMF components by comparing feature indexes such as variance and root mean square value.…”