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Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis

Gu, Fengshou, Tian, Xiange, Chen, Zhi, Rehab, Ibrahim and Ball, Andrew (2014) Fault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis. International journal of structural analysis & design, 1 (2). ISSN 2372 - 4102

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Abstract

Faults in rolling element bearing are among the main causes of breakdown in rotating machines. Vibration is an effective technique for machine condition monitoring. Vibration signals from a defective bearing with a localized fault contain a series of impulsive responses, which result from the impacts of the defective part(s) with other elements. Most researches carried out have focused on fault location identification. However, limited work has been reported for fault severity estimation, which is critical to make decision for maintenance actions. To improve current diagnostic capability, this paper pays more attention to bearing fault severity diagnosis. It models the vibration sources from bearing defects as an impact process with constant size but three different lengths corresponding to outer race fault, inner race fault and roller fault, respectively. Then an experimental study was followed to evaluate this model. Moreover, the conventional envelope analysis of the measured vibration signals from the tested faulty bearings is optimized by spectral kurtosis (SK) for automatic and reliable fault detection and fault category diagnosis. In the meantime, the diagnostic parameters for fault severity estimation: root mean squared (RMS) values and kurtosis amplitude are developed based on the model results and subsequently evaluated to be agreed vigorously with tested fault cases.

Item Type: Article
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
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Depositing User: Cherry Edmunds
Date Deposited: 02 Jul 2014 13:00
Last Modified: 30 Nov 2016 19:40
URI: http://eprints.hud.ac.uk/id/eprint/21093

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