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Fault Detection of Rolling Element Bearings Using the Frequency Shift and Envelope based Compressive Sensing

Tang, Xiaoli, Xu, Yuandong, Gu, Fengshou and Wang, Guangbin (2017) Fault Detection of Rolling Element Bearings Using the Frequency Shift and Envelope based Compressive Sensing. Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). ISSN 9780701702601

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Rolling element bearings are the essential components of rotating machines, faults of which can cause serious failures or even major breakdowns of a machine. Fault diagnosis deliveries significant benefits to machines with rolling element bearings by finding the faults at early period and taking corrective actions to enhance safe and high performance operations. However, multiple sensor usages and high rate data acquisition involved in a monitoring system have considerable drawbacks of high system cost involved in purchasing hardware for data transfer, storage and processing. To reduce these shortages, this paper investigates compressive sensing (CS) techniques for the fault detection of rolling element bearings. Based on the frequency shift and envelope analysis, a CS scheme is developed for monitoring the bearing. The number of data transmitted and stored can be reduced by several thousands of times. The simulation and the experimental results demonstrate that the compressed vibration signals of rolling element bearings are effective to detect bearing faults at the total compressing ratio up to several thousand with the corresponding maximum compression ratio (CR) of CS process at nearly 100. In addition, several performance measures are applied to evaluate the reconstructed signals and show approximately the information about the noise level of the system.

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: Rolling element bearings; Compressive sensing; Frequency shift; Reconstruction
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: 09 Oct 2017 09:53
Last Modified: 28 Aug 2021 15:30


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