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The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines
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Research works printed but not linked: 6
- Randall, 2001, The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine, Mechanical Systems and Signal Processing, 5, 945, 10.1006/mssp.2001.1415 · DOI · Paper page
- Antoni, 2002, Differential diagnosis of gear and bearing faults, ASME Journal of Vibration and Acoustics, 124, 165, 10.1115/1.1456906 · DOI · Paper page
- Ho, 2000, Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals, Mechanical Systems and Signal Processing, 14, 763, 10.1006/mssp.2000.1304 · DOI · Paper page
- Tse, 2001, Wavelet analysis and envelope detection for rolling element bearing fault diagnosis—their effectiveness and flexibility, Transactions of the ASME, Journal of Vibration and Acoustics, 123, 303, 10.1115/1.1379745 · DOI · Paper page
- Altmann, 2001, Multiple band-pass autoregressive demodulation for rolling-element bearing fault diagnosis, Mechanical Systems and Signal Processing, 15, 963, 10.1006/mssp.2001.1410 · DOI
- Nikolaou, 2002, Demodulation of vibration signals generated by defects in rolling element bearings using complex shifted morlet wavelets, Mechanical Systems and Signal Processing, 16, 677, 10.1006/mssp.2001.1459 · DOI
Cited by
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
Self-citationA review on signal processing techniques utilized in the fault diagnosis of rolling element bearings
Rai, A., & Upadhyay, S. H. (2016) · Tribology International · doi:10.1016/j.triboint.2015.12.037 · Cited by 804
Improvement of kurtosis-guided-grams via Gini index for bearing fault feature identification
Miao, Y., Zhao, M., & Lin, J. (2017) · Measurement Science and Technology · doi:10.1088/1361-6501/aa8a57 · Cited by 282
Wang, S., Xiang, J., Zhong, Y., & Zhou, Y. (2018) · Knowledge-Based Systems · doi:10.1016/j.knosys.2017.12.027 · Cited by 269
Abboud, D., Antoni, J., Sieg-Zieba, S., & Eltabach, M. (2017) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2016.06.033 · Cited by 177
Self-citation
Metadata
- Authors
- Antoni, J., & Randall, R. B.
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2006-02
- Volume
- 20
- Issue
- 2
- Pages
- 308-331
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W1985110006
- Cited by
- 1,333
- References
- 0
- FWCI
- 14.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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- CoChat. (2026). Citation check: The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines. https://app.cochat.ai/papers/10.1016/j.ymssp.2004.09.002
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- Antoni, J., & Randall, R. B. (2006). The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines. Mechanical Systems and Signal Processing. https://doi.org/10.1016/j.ymssp.2004.09.002
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.
