Abstract
Acoustic Emission (AE) Method is widely used in research for machinery diagnostics, and wavelet transform has been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether the acoustic signal can be used effectively to detect the fault in rolling element bearing using discrete wavelet transform (DWT). A novel mother function for DWT was extracted through acoustic signal measured by the fatigue crack growth test. A commonly encountered fault was simulated. The results suggest that DWT applied using the novel mother function is an effective for the detection of fault and may provide a powerful tool to indicate the faults in rolling element bearing.
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