Abstract
Surface contact fatigue is one of the most common failures of rolling element bearings. The initialization and propagation of subsurface cracks during early fatigue damages produce acoustic emission (AE) signals. Hence it has the advantage to detect early faults by acoustic emission monitoring technology. In this chapter, acoustic emission signal and vibration signal were collected during fatigue damage experiment of rolling element bearing in a self-made test rig. A number of data-processing methods were used here, such as kurtosis, RMS, and information entropy, to analyze the signal. The experiment indicated that the fault characteristic frequency of AE signal is more significant than that of vibration signal, and AE signal has a higher signal-to-noise ratio than vibration signal, so it is much earlier and more sensitive in detecting the degradation of surface contact fatigue.
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