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28 December 2020 Application of a Wavelet Transform after Signal Differentiation in Fault Diagnosis
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Abstract

Yuan, X.; Wu, W.; Ye, F.; Chou, S., and Lee, Z., 2020. Application of a wavelet transform after signal differentiation in fault diagnosis. In: Hu, C. and Cai, M. (eds.), Geo-informatics and Oceanography. Journal of Coastal Research, Special Issue No. 105, pp. 61–66. Coconut Creek (Florida), ISSN 0749-0208.

Differential operations have different effects on various signal transformations. As a powerful signal processing method, wavelet transform has an efficient effect on signal analysis. In this paper, the collected mechanical signals are used to transform the original signal and the differentiated signal by wavelet transform, features are extracted, and then the clustering method is used to identify faults. The experimental results show that the differential method helps improve the accuracy of fault diagnosis. The reason is that the differential changes the frequency factor in the wavelet transform result, and this frequency factor has been experimentally proven to have a certain effect on the signal analysis result.

©Coastal Education and Research Foundation, Inc. 2020
Xiaojian Yuan, Wenbing Wu, Fulan Ye, SoTsung Chou, and Znejung Lee "Application of a Wavelet Transform after Signal Differentiation in Fault Diagnosis," Journal of Coastal Research 105(sp1), 61-66, (28 December 2020). https://doi.org/10.2112/JCR-SI105-013.1
Received: 2 July 2020; Accepted: 27 July 2020; Published: 28 December 2020
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