Research on the prediction algorithm of aero engine lubricating oil consumption based on multi-feature information fusion
Author:
Funder
National Science and Technology Major Project
National Major Science and Technology Projects of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05759-6.pdf
Reference45 articles.
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3. Zhao J, Li YG, Sampath S (2023) A hierarchical structure built on physical and data-based information for intelligent aero-engine gas path diagnostics. Appl Energy 332:120520
4. Li Y, Chen Y, Hu Z et al (2023) Remaining useful life prediction of aero-engine enabled by fusing knowledge and deep learning models[J]. Reliab Eng Syst Saf 229:108869
5. Li Y, Zhang Y, Guo Z, Wang A (2023) Fault diagnosis of aero-engine lubrication system based on KPCA-ABC-SVM[C]//2023 prognostics and health management conference (PHM). IEEE 6–11
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