ROTATING MACHINERY FAULT DETECTION BASED ON IMPROVED ENSEMBLE EMPIRICAL MODE DECOMPOSITION

Abstract

An improved EEMD approach is introduced in this paper based on automatically obtaining the adding white noise amplitude and the ensemble number according to different analyzing signal characteristics. The adding white noise affects decomposition effect is researched in detail, a criterion of adding white noise in EEMD is established, and the improved EEMD algorithm is described. Simulated signals demonstrate the effectiveness of the improved EEMD in diagnosing the faults of rotating machinery. The improved EEMD is successfully applied to an early rub-impact fault detection of machine unit for catalytic cracking of heavy oil, with the fault reason being analyzed in detail. A gear fault detection of hot strip finishing mills is also analyzed utilizing the improved EEMD method. The results show that the improved EEMD can obtain more precise diagnosis results than the original EMD and FFT spectrum.