Acoustic signature based early fault detection in rolling element bearings
© 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 shoul...
| Main Authors: | , , , , , |
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| Format: | Book Chapter |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/71302 |
| _version_ | 1848762444144443392 |
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| author | Najafi Amin, Amir McKee, Kristoffer Mazhar, Ilyas Bredin, Arne Mullins, Ben Howard, Ian |
| author_facet | Najafi Amin, Amir McKee, Kristoffer Mazhar, Ilyas Bredin, Arne Mullins, Ben Howard, Ian |
| author_sort | Najafi Amin, Amir |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 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. |
| first_indexed | 2025-11-14T10:47:40Z |
| format | Book Chapter |
| id | curtin-20.500.11937-71302 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:47:40Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-713022021-02-16T07:49:42Z Acoustic signature based early fault detection in rolling element bearings Najafi Amin, Amir McKee, Kristoffer Mazhar, Ilyas Bredin, Arne Mullins, Ben Howard, Ian © 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. 2019 Book Chapter http://hdl.handle.net/20.500.11937/71302 10.1007/978-3-319-95711-1_41 restricted |
| spellingShingle | Najafi Amin, Amir McKee, Kristoffer Mazhar, Ilyas Bredin, Arne Mullins, Ben Howard, Ian Acoustic signature based early fault detection in rolling element bearings |
| title | Acoustic signature based early fault detection in rolling element bearings |
| title_full | Acoustic signature based early fault detection in rolling element bearings |
| title_fullStr | Acoustic signature based early fault detection in rolling element bearings |
| title_full_unstemmed | Acoustic signature based early fault detection in rolling element bearings |
| title_short | Acoustic signature based early fault detection in rolling element bearings |
| title_sort | acoustic signature based early fault detection in rolling element bearings |
| url | http://hdl.handle.net/20.500.11937/71302 |