Abstract
A method based on a fractal theory and Wavelet Transform applied to fault detection in roller element bearings is introduced. The Orthogonal Wavelet Transform is used to decompose a vibration based signal into scale components in order to reveal self-similarities in the signal. For fault detection the wavelet coefficient variance plots both for reference and damaged data are calculated and compared. The studies are based on simulated data and real life case from a wind turbine.
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Ziaja, A., Barszcz, T., Staszewski, W. (2012). Fractal Based Signal Processing for Fault Detection in Ball-Bearings. In: Fakhfakh, T., Bartelmus, W., Chaari, F., Zimroz, R., Haddar, M. (eds) Condition Monitoring of Machinery in Non-Stationary Operations. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28768-8_41
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DOI: https://doi.org/10.1007/978-3-642-28768-8_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28767-1
Online ISBN: 978-3-642-28768-8
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