Gear failure prediction using multiscale local statistics

In this work, multiscale local statistics are introduced as a tool for gear failure prediction. Experimental data from gears with localized defects in the form of bending fatigue cracks were analysed. It was shown that second order central moments increased with defect magnitude. The estimation proc...

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Bibliographic Details
Published in:Engineering structures 2008-05, Vol.30 (5), p.1214-1223
Main Author: Loutridis, S.J.
Format: Article
Language:English
Subjects:
Applied sciences
Drives
Exact sciences and technology
Gear failure prediction
Gears
Local variance
Mechanical engineering. Machine design
Multiscale statistics
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Summary:In this work, multiscale local statistics are introduced as a tool for gear failure prediction. Experimental data from gears with localized defects in the form of bending fatigue cracks were analysed. It was shown that second order central moments increased with defect magnitude. The estimation procedure was carried out in the range of scales where the defect is more prominent. An empirical law that relates variance at various scales to crack magnitude was established. Compared to the wavelet transform, the multiscale statistical scheme is an attractive option due to its low complexity, high sensitivity and inherent robustness.
ISSN:0141-0296
1873-7323
DOI:10.1016/j.engstruct.2007.07.022