Ten lectures on wavelets
An introduction to wavelets
A new subclass of complex-valued S-transform windows
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Localization of the complex spectrum: the S transform
IEEE Transactions on Signal Processing
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This paper describes the use of the S-Transform to identify fatigue features in variable amplitude loadings. For this case, this type of loading exhibits nonstationary signal pattern, for which a normal frequency domain analysis cannot provide an accurate results for the analysis. In order to overcome this problem, the time-localisation approach provides a promising answer. A variable amplitude fatigue loading, which was measured from a lower suspension arm of a vehicle driven over a test track, was used for the analysis of this study. In order to identify fatigue damaging events, the data was processed using the orthogonal wavelet based algorithm, or known as Wavelet Bump Extraction (WBE). Since the S-transform if the simplification of the wavelet transform, it is a good idea to explore this transform to help the identification of these fatigue features. The results from the computational analysis results showed that the high amplitude events were detected in the variable amplitude loading based on the difference pattern of the time-frequency localisation. From the findings of this paper, it is suggested that further developments in the S-transform will find applications in a broad research area, particularly in the fatigue life assessment.