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Fault Classification and Fault Signature Production for Rolling Element Bearings in Electric Machines
Abstract
Most condition monitoring techniques for rolling element bearings are designed to detect the four characteristic fault frequencies. This has lead to the common practice of categorizing bearing faults according to fault location (i.e., inner race, outer race, ball, or cage fault). While the ability to detect the four characteristic fault frequencies is necessary, this approach neglects another important class of faults that arise in many industrial settings. This research introduces the notion of categorizing bearing faults as either single-point defects or generalized roughness. These classes separate bearing faults according to the fault signatures that are produced rather than by the physical location of the fault. Specifically, single-point defects produce the four predictable characteristic fault frequencies while faults categorized as generalized roughness produce unpredictable broadband changes in the machine vibration and stator current. Experimental results are provided from bearings failed in situ via a shaft current. These results illustrate the unpredictable and broadband nature of the effects produced by generalized roughness bearing faults. This issue is significant because a successful bearing condition monitoring scheme must be able to reliably detect both classes of faults.
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Citations
Cited by
Review of condition monitoring of rotating electrical machines
Tavner, P. J. (2008) · IET Electric Power Applications · doi:10.1049/iet-epa:20070280 · Cited by 531
Immovilli, F., Bellini, A., Rubini, R., & Tassoni, C. (2010) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2010.2049623 · Cited by 382
Rosero, J., Romeral, J. L., Cusido, J., Ortega, J. A., & Garcia, A. (2008) · 2008 Twenty-Third Annual IEEE Applied Power Electronics Conference and Exposition · doi:10.1109/apec.2008.4522708 · Cited by 44
Metadata
- Authors
- Stack, J. R., Habetler, T. G., & Harley, R. G.
- Venue
- IEEE Transactions on Industry Applications
- Published
- 2004-05
- Volume
- 40
- Issue
- 3
- Pages
- 735-739
- ISSN
- 0093-9994 (ISSN-L)
- OpenAlex
- W1985965778
- Cited by
- 290
- References
- 0
- FWCI
- 16.41
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Fault Classification and Fault Signature Production for Rolling Element Bearings in Electric Machines. https://app.cochat.ai/papers/10.1109/tia.2004.827454
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- Stack, J. R., Habetler, T. G., & Harley, R. G. (2004). Fault Classification and Fault Signature Production for Rolling Element Bearings in Electric Machines. IEEE Transactions on Industry Applications. https://doi.org/10.1109/tia.2004.827454
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