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Model Based Approach for Identification of Gears and Bearings Failure Modes

Author(s): Renata Klein | Eduard Rudyk | Eyal Masad | Moshe Issacharoff

Journal: International Journal of Prognostics and Health Management
ISSN 2153-2648

Volume: 2;
Issue: 2;
Start page: 17;
Date: 2011;
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Keywords: Data-driven methods for fault detection | diagnosis | prognosis

This paper describes the algorithms that were used for analysis of the PHM’09 gear-box. The purpose of the analysis was to detect and identify faults in various components of the gear-box. Each of the 560 vibration recordings presented a different set of faults, including distributed and localized gear faults, typical bearing faults and shaft faults. Each fault had to be pinpointed precisely.In the following sections we describe the algorithms used for finding faults in bearings, gears and shafts, and the conclusions that were reached. A special blend of pattern recognition and signal processing methods was applied.Bearings were analyzed using the orders representation of the envelope of a band pass filtered signal and an envelope of the de-phased signal. A special search algorithm was applied for bearings features extraction. The diagnostics of the bearings failure modes was carried out automatically. Gears were analyzed using the order domains, the quefrency of orders, and the derivatives of the phase average.
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