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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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/61339/ http://eprints.utm.my/61339/ |
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| Summary: | 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. |
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