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The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators

Li, Long, Wang, Guangbin, Deng, Wenhui, Tang, Xiaoli, Gu, Fengshou and Ball, Andrew (2017) The Identification of Shaft Current Induced Defects on Rolling Bearings in Wind Turbine Generators. Proceedings of the 23rd International Conference on Automation & Computing (University of Huddersfield, 7-8 September 2017).

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Abstract

Rolling bearings are an important part of wind turbine systems. Shaft current induced damages are one of the main causes for bearing failures, which lead to considerable operation loss of wind turbine plants. In this paper, the characteristics of shaft current damages and their induced vibration responses are studied analytically. Then it suggests to use an emerging Modulation Signal Bispectrum (MSB) to detect and diagnose the incipient defects as MSB can suppress various noise and provide a sparse result that integrates particularly the fault modulator and the structural resonance carrier to highlight the fault effect. Finally, the detection and diagnosis results based on both simulated signals and experimental signals show the outstanding performance of MSB analysis in detecting common bearing faults. Especially, it can achieve a straightforward differentiation between the fatigue pitting defects and shaft current damages, whereas conventional envelope analysis cannot provide a separation between these two types.

Item Type: Article
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Shaft current; Bearing fault diagnosis; Envelope spectrum; MSB
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Schools: School of Computing and Engineering
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Depositing User: Jonathan Cook
Date Deposited: 05 Oct 2017 12:14
Last Modified: 12 Dec 2017 01:10
URI: http://eprints.hud.ac.uk/id/eprint/33632

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