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17 May 2005 Generalized harmonic wavelet as an adaptive filter for machine health diagnosis
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This paper presents an adaptive filtering technique for the health diagnosis of mechanical systems, based on the generalized harmonic wavelet transformation. Through selection of two wavelet level parameters, a series of sub-frequency band wavelet coefficients corresponding to equi-bandwidth vibration signals measured from a machine were constructed. The energy and entropy associated with each sub-frequency band were then calculated, and the band with the maximum energy-to-entropy ratio was chosen to form a band-limited filter for the vibration signals. Experimental studies using rolling bearings that contain structural defects have confirmed that, the developed new technique enables high signal-to-noise ratio for effective machine failure detection and health diagnosis.
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Ruqiang Yan and Robert X. Gao "Generalized harmonic wavelet as an adaptive filter for machine health diagnosis", Proc. SPIE 5765, Smart Structures and Materials 2005: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (17 May 2005);


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