A Comparative Study of Reassigned Conventional Wavelet Transform for Machinery Faults Detection

Application of Fast Fourier Transform (FFT) in machinery faults detection is known to be only effective if fault is of repetitive in nature and considering severe. While minor and transient faults are usually remain undetected based on vibration spectrum analysis. Wavelet analysis is relatively new...

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Veröffentlicht in:Applied Mechanics and Materials 2015-07, Vol.773-774 (International Integrated Engineering Summit 2014), p.90-94
Hauptverfasser: Hee, Lim Meng, Leong, M. Salman, Abdelrhman, Ahmed M., Ngui, Wai Keng
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Sprache:eng
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Zusammenfassung:Application of Fast Fourier Transform (FFT) in machinery faults detection is known to be only effective if fault is of repetitive in nature and considering severe. While minor and transient faults are usually remain undetected based on vibration spectrum analysis. Wavelet analysis is relatively new technique which is still suffered from inadequately in its time-frequency resolution. In this paper, ahmedrabak_time wavelet is proposed based on the wavelet reassignment technique for Morlet mother wavelet. The proposed wavelet analysis is compared to the conventional wavelet analysis for machinery faults detection based on simulated signal. The results showed that the proposed wavelet has a better resolution than conventional wavelet analysis which could clearly indicate the presence and the location of the fault.
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.773-774.90