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.
|Title of host publication
|Proceedings of the 23rd International Conference on Automation and Computing (University of Huddersfield, 7-8 September 2017)
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 26 Oct 2017
|23rd International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing - University of Huddersfield, Huddersfield, United Kingdom
Duration: 7 Sep 2017 → 8 Sep 2017
Conference number: 23
https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)
|23rd International Conference on Automation and Computing
|7/09/17 → 8/09/17
|The scope of the conference covers a broad spectrum of areas with multi-disciplinary interests in the fields of automation, control engineering, computing and information systems, ranging from fundamental research to real-world applications.