Advanced signal processing techniques for wind turbine gearbox bearing failure detection

Abstract

Premature wind turbine gearbox failure has been observed to occur after periods as short as 5 years, while the design life of a gearbox is expected to exceed 20 years. Most wind turbine failures have been found to be initiated at the bearings. The formation of white etching cracks (WECs) on the subsurface of bearings can occur after 6 months to 2 years of operation. WECs, which can eventually lead to spallation and catastrophic failure of the wind turbine gearbox, have been identified as one of the most severe damaging causes of failure in bearings. Recent research has suggested that electrical load is one of the key parameters affecting the formation of WECs. To investigate the characteristics and formation of WECs, a test rig was designed at the University of Erlangen-Nuremberg. The rig facilitated the simultaneous data capture of vibration, electrostatic and acoustic emission through dedicated sensors. Signal processing techniques have been utilised to process and correlate sensor data in order to detect WECs before the final failure occurs and trace back to earlier stages of propagation. This conference paper demonstrates the effectiveness of the suggested signal processing techniques, using multiple sensors, to detect and monitor bearing crack initiation and propagation.

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Identifiers

ORCID for Ling Wang: orcid.org/0000-0002-2894-6784

ORCID for Neil White: orcid.org/0000-0003-1532-6452

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