Detection and diagnosis of bearing faults using shift-invariant dictionary learning and hidden Markov model
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Hidden Markov models are considered as classifiers in health state recognition of bearings, synchronous motors, and hydraulic pumps.
“Furthermore, the hidden Markov models are considered as classifiers in the health state recognition of bearings [291][292][293][294][295], the synchronous motors [296], and the hydraulic pumps [297].”
From Applications of machine learning to machine fault diagnosis: A review and roadmap (2020) · cites this paper as [292]
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Applications of machine learning to machine fault diagnosis: A review and roadmap
Lei, Y., Yang, B., Jiang, X., Jia, F., Li, N., & Nandi, A. K. (2020) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2019.106587 · Cited by 2,997 · see citing works
Liu, R., Meng, G., Yang, B., Sun, C., & Chen, X. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2016.2645238 · Cited by 345 · see citing works
- Authors
- Zhou, H., Chen, J., Dong, G., & Wang, R.
- Affiliations
- Shanghai Jiao Tong University (CN)
- Shanghai Maritime University (CN)
- Corresponding author
- Zhou, Haitao
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2016-05
- Volume
- 72-73
- Pages
- 65-79
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W2189028327
- Cited by
- 131
- References
- 41
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 7 · 2023: 13 · 2022: 8 · 2021: 17 · 2020: 15 · 2019: 15 · 2018: 17 · 2017: 20 · 2016: 8
- FWCI
- 13.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Mechanical Systems and Signal Processing (publishedVersion)
- Funders
- National Natural Science Foundation of China (51575339)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Physical Sciences › Engineering › Mechanical Engineering › Gear and Bearing Dynamics Analysis
- Keywords
- bearing fault diagnosis, hidden Markov models, adaptive feature extraction, mechanical fault diagnosis, fault classification
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