Abstract
In this paper we propose an approach for gear fault prognostics in presumably non-stationary and unknown operating conditions. The approach monitors the evolution of the statistical complexity of the generated vibrations envelope vis-à-vis its Rényi entropy. The statistical complexity is obtained through the wavelet coefficients calculated from the generated vibrations. Such an approach allows seamless estimation of the remaining useful life of the monitored drive without any prior information about the operating conditions and no a priori data regarding the physical characteristics of the monitored drive. The effectiveness of the approach was evaluated on experiments monitoring natural gear fault progress under variable load.
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Boškoski, P., Juričić, Đ. (2012). Rényi Entropy Based Statistical Complexity Analysis for Gear Fault Prognostics under Variable Load. 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_3
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DOI: https://doi.org/10.1007/978-3-642-28768-8_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28767-1
Online ISBN: 978-3-642-28768-8
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