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An ensemble learning-based prognostic approach with degradation-dependent weights for remaining useful life prediction

  • Published:2019-04 Issue: Volume:184 Page:110-122
  • ISSN:0951-8320
  • Container-title:Reliability Engineering & System Safety
  • language:en
  • Short-container-title:Reliability Engineering & System Safety

Author:

Li Zhixiong,Wu Dazhong,Hu Chao,Terpenny Janis

Funder

National Science Foundation

U.S. Department of Transportation

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Reference50 articles.

1. Condition monitoring and diagnostics of machines—prognostics—part 1: general guidelines,2004

2. A review on the key issues for lithium-ion battery management in electric vehicles;Lu;J Power Sources,2013

3. Prognostics and health management of electronics;Pecht,2008

4. Review of hybrid prognostics approaches for remaining useful life prediction of engineered systems, and an application to battery life prediction;Liao;IEEE Trans Reliab,2014

5. A particle filtering approach for on-line failure prognosis in a planetary carrier plate;Orchard;Int J Fuzzy Logic Intell Syst,2007

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