The DOI matches its Crossref record; 143 of the 143 references it cites were found in a registry or an index.
A summary of fault modelling and predictive health monitoring of rolling element bearings
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Citations
Cites
A review on machinery diagnostics and prognostics implementing condition-based maintenance
Jardine, A. K. S., Lin, D., & Banjevic, D. (2006) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2005.09.012 · Cited by 4,816
Rolling element bearing diagnostics—A tutorial
Randall, R. B., & Antoni, J. (2011) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2010.07.017 · Cited by 2,744
The spectral kurtosis: a useful tool for characterising non-stationary signals
Antoni, J. (2006) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2004.09.001 · Cited by 1,441
Tandon, N., & Choudhury, A. (1999) · Tribology International · doi:10.1016/s0301-679x(99)00077-8 · Cited by 1,351
Antoni, J., & Randall, R. B. (2006) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2004.09.002 · Cited by 1,333
Rotating machinery prognostics: State of the art, challenges and opportunities
Heng, A., Zhang, S., Tan, A. C. C., & Mathew, J. (2009) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2008.06.009 · Cited by 1,207
Peng, Z. K., & Chu, F. L. (2004) · Mechanical Systems and Signal Processing · doi:10.1016/s0888-3270(03)00075-x · Cited by 1,192
A Survey of Dimension Reduction Techniques
Fodor, I. K. (2002) · doi:10.2172/15002155 · Cited by 1,116
Model for the vibration produced by a single point defect in a rolling element bearing
McFadden, P. D., & Smith, J. D. (1984) · Journal of Sound and Vibration · doi:10.1016/0022-460x(84)90595-9 · Cited by 931
FEATURE EXTRACTION BASED ON MORLET WAVELET AND ITS APPLICATION FOR MECHANICAL FAULT DIAGNOSIS
LIN, J., & QU, L. (2000) · Journal of Sound and Vibration · doi:10.1006/jsvi.2000.2864 · Cited by 879
Cited by
Ferreira, C., & Gonçalves, G. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.05.010 · Cited by 417
Deep learning for infrared thermal image based machine health monitoring
Janssens, O., Van de Walle, R., Loccufier, M., & Van Hoecke, S. (2018) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2017.2722479 · Cited by 207
Diagnosis of stator faults of the single-phase induction motor using acoustic signals
Glowacz, A., & Glowacz, Z. (2017) · Applied Acoustics · doi:10.1016/j.apacoust.2016.10.012 · Cited by 124
Metadata
- Authors
- El-Thalji, I., & Jantunen, E.
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2015-08
- Volume
- 60-61
- Pages
- 252-272
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W1967116388
- Cited by
- 447
- References
- 143
- FWCI
- 37.12
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A summary of fault modelling and predictive health monitoring of rolling element bearings. https://app.cochat.ai/papers/10.1016/j.ymssp.2015.02.008
- The paper
- El-Thalji, I., & Jantunen, E. (2015). A summary of fault modelling and predictive health monitoring of rolling element bearings. Mechanical Systems and Signal Processing. https://doi.org/10.1016/j.ymssp.2015.02.008
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
