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dc.contributor.authorNajafi Amin, Amir
dc.contributor.authorMcKee, Kristoffer
dc.contributor.authorMazhar, Ilyas
dc.contributor.authorBredin, Arne
dc.contributor.authorMullins, Ben
dc.contributor.authorHoward, Ian
dc.date.accessioned2018-12-13T09:09:36Z
dc.date.available2018-12-13T09:09:36Z
dc.date.created2018-12-12T02:46:39Z
dc.date.issued2019
dc.identifier.citationNajafi Amin, A. and McKee, K. and Mazhar, I. and Bredin, A. and Mullins, B. and Howard, I. 2019. Acoustic signature based early fault detection in rolling element bearings. In Lecture Notes in Mechanical Engineering, 415-422.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/71302
dc.identifier.doi10.1007/978-3-319-95711-1_41
dc.description.abstract

© Springer Nature Switzerland AG 2019. Early fault detection in rotary machines can reduce the maintenance cost and avoid unexpected failure in the production line. Vibration analysis can diagnose some of the common faults inside the rolling element bearings; however, the vibration measurement should be taken from a transducer that is located on the bearing or very close to the supporting structure, which is sometimes not feasible. This study compares acoustic and vibration signature-based methods for detecting faults inside the bearings. It uses both time and frequency based fault indicators (i.e. RMS, Kurtosis and envelope analysis) for investigating the condition of the system. Experiments were carried out on a belt-drive system with three different bearing conditions (normal, corroded and outer race fault). The experimental results show acoustic signature-based methods can detect the system’s fault from close distances, and even for relatively far distance, some bearing conditions are still detectable.

dc.titleAcoustic signature based early fault detection in rolling element bearings
dc.typeBook Chapter
dcterms.source.startPage415
dcterms.source.endPage422
dcterms.source.titleLecture Notes in Mechanical Engineering
curtin.departmentSchool of Civil and Mechanical Engineering (CME)
curtin.accessStatusFulltext not available
curtin.contributor.orcidHoward, Ian [0000-0003-3999-9184]


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