Fault Detection of Rotating Machinery from Bicoherence Analysis of Vibration Data
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Citation for Previous Publication
Halim, E., Choudhury, M., Shah, S., and Zuo, M. (2006). Fault Detection of Rotating Machinery from Bicoherence Analysis of Vibration Data. IFAC Proceedings Volumes, 39(13), 1348-1353.
Link to Related Item
http://dx.doi.org/10.3182/20060829-4-CN-2909.00225
Abstract
Description
The vibration signal carries the signature of faults in most rotating equipments, and early fault detection is possible by analyzing the signal using different signal processing techniques. In this paper we consider a gearbox as a typical representation of a rotating or cyclo-stationary process. Faults in gearboxes leave their signature on the vibration signal and generally manifest themselves as a non-linear transformation in the signal. Bicoherence analysis detects and quantifies the presence of non-linearity in the signal and thus indicates the severity of the fault in the gearbox. In this work, time synchronous averaging is used to find the proper representation of one period of the cyclo-stationary vibration signal. A pilot scale gearbox case study is presented to demonstrate the practicality and utility of the proposed technique.
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http://purl.org/coar/resource_type/R60J-J5BD
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© 2006 IFAC. This version of this article is open access and can be downloaded and shared. The original author(s) and source must be cited.
Language
en