Abstract
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.
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