Harmonic wavelet-based data filtering for enhanced machine defect identification

Abstract

A filter construction technique is presented for enhanced defect identification in rotary machine systems. Based on the generalized harmonic wavelet transform, a series of sub-frequency band wavelet coefficients are constructed by choosing different harmonic wavelet parameter pairs. The energy and entropy associated with each sub-frequency band are then calculated. The filtered signal is obtained by choosing the wavelet coefficients whose corresponding sub-frequency band has the maximum energy-to-entropy ratio. Experimental studies using rolling bearings that contain different types of structural defects have confirmed that the developed new technique enables high signal-to-noise ratio for effective machine defect identification.