The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Remaining useful life prediction of aircraft engine based on degradation pattern learning
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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
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
Damage propagation modeling for aircraft engine run-to-failure simulation
Saxena, A., Goebel, K., Simon, D., & Eklund, N. (2008) · 2008 International Conference on Prognostics and Health Management · doi:10.1109/phm.2008.4711414 · Cited by 1,954
Rezvanizaniani, S. M., Liu, Z., Chen, Y., & Lee, J. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.01.085 · Cited by 684
Recurrent neural networks for remaining useful life estimation
Heimes, F. O. (2008) · 2008 International Conference on Prognostics and Health Management · doi:10.1109/phm.2008.4711422 · Cited by 644
Liao, L., & Kottig, F. (2014) · IEEE Transactions on Reliability · doi:10.1109/tr.2014.2299152 · Cited by 563
Residual Life Predictions From Vibration-Based Degradation Signals: A Neural Network Approach
Gebraeel, N., Lawley, M., Liu, R., & Parmeshwaran, V. (2004) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2004.824875 · Cited by 557
He, W., Williard, N., Chen, C., & Pecht, M. (2014) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2014.04.059 · Cited by 539
Ben Ali, J., Chebel-Morello, B., Saidi, L., Malinowski, S., & Fnaiech, F. (2015) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2014.10.014 · Cited by 502
A similarity-based prognostics approach for Remaining Useful Life estimation of engineered systems
Wang, T., Yu, J., Siegel, D., & Lee, J. (2008) · 2008 International Conference on Prognostics and Health Management · doi:10.1109/phm.2008.4711421 · Cited by 474
Cited by
Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2020) · Frontiers in Mechanical Engineering · doi:10.3389/fmech.2020.578379 · Cited by 70
Metadata
- Authors
- Zhao, Z., Liang, B., Wang, X., & Lu, W.
- Venue
- Reliability Engineering & System Safety
- Publisher
- Elsevier BV
- Published
- 2017-08
- Volume
- 164
- Pages
- 74-83
- ISSN
- 0951-8320 (ISSN-L)
- OpenAlex
- W2594845301
- Cited by
- 267
- References
- 36
- FWCI
- 13.26
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Remaining useful life prediction of aircraft engine based on degradation pattern learning. https://app.cochat.ai/papers/10.1016/j.ress.2017.02.007
- The paper
- Zhao, Z., Liang, B., Wang, X., & Lu, W. (2017). Remaining useful life prediction of aircraft engine based on degradation pattern learning. Reliability Engineering & System Safety. https://doi.org/10.1016/j.ress.2017.02.007
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.
