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In condition monitoring and fault diagnosis of machinery, vibration analysis is the major method and wavelet analysis is widely implemented. The acoustic emission (AE) method is another important and effective signal in fault diagnosis of mechanical systems. In this paper, the AE signal is applied to diagnose the piston condition of the water hydraulic motor in a water hydraulic system. The AE signal is obtained under different flow rates and torques. The wavelet-based signal processing technique is used to analyze the fluid-borne vibration and structure-borne vibration (acoustic signal). The spectrum based on wavelet analysis is effective in analyzing the acoustic signals under specific frequency ranges, compared with the conventional power spectrum density (PSD). The results show root mean square (RMS) of the wavelet-based acoustic signal analysis is very effective for the fault diagnosis of piston cracks under the different flow rates and torques.
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Chen et al. (2008) studied this question.
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