Application of Local Mean Decomposition to Acoustic Emission Data for Natural Fatigue Cracks Feature Extraction in Rotating Shafts

Yue Zhou, Lin Li, Zhou Yong


This paper presents the results of applying recently developed local mean decomposition (LMD), a new iterative approach to acoustic emission(AE) feature extraction of natural fatigue cracks in rotating shafts providing an energy-frequency-time distribution with more adaptable precision. The method decomposes AE signals into a set of functions, each of which is the product of an envelope signal and a frequency modulated signal from which a time-varying instantaneous frequency can be derived. It has been found that LMD appears to be a better tool providing an energy-frequency-time distribution compared to Hilbert–Huang transform (HHT) for natural fatigue crack characterization in a rotating rotor in the experiment cases. It was concluded that LMD-based AE technology could more successfully extract the features of natural fatigue cracks induced on rotating shafts.


Index Terms—Local Mean Decomposition, Acoustic Emission, Fatigue Crack, Feature Extraction


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