The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A segmental hidden semi-Markov model (HSMM)-based diagnostics and prognostics framework and methodology
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Citations
Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
Explicit modelling of state occupancy in hidden Markov models for automatic speech recognition
Russell, M., & Moore, R. (1985) · ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing · doi:10.1109/icassp.1985.1168477 · Cited by 194
Cited by
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
Lei, Y., Li, N., Guo, L., Li, N., Yan, T., & Lin, J. (2018) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2017.11.016 · Cited by 2,634
Remaining useful life estimation – A review on the statistical data driven approaches
Si, X.-S., Wang, W., Hu, C.-H., & Zhou, D.-H. (2011) · European Journal of Operational Research · doi:10.1016/j.ejor.2010.11.018 · Cited by 2,162
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
Yu, S.-Z. (2010) · Artificial Intelligence · doi:10.1016/j.artint.2009.11.011 · Cited by 734
Remaining useful life prediction of aircraft engine based on degradation pattern learning
Zhao, Z., Liang, B., Wang, X., & Lu, W. (2017) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2017.02.007 · Cited by 267
Metadata
- Authors
- Dong, M., & He, D.
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2007-07
- Volume
- 21
- Issue
- 5
- Pages
- 2248-2266
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W1992113394
- Cited by
- 318
- References
- 2
- FWCI
- 7.62
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Dong, M., & He, D. (2007). A segmental hidden semi-Markov model (HSMM)-based diagnostics and prognostics framework and methodology. Mechanical Systems and Signal Processing. https://doi.org/10.1016/j.ymssp.2006.10.001
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.
