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Remaining useful life estimation using an inverse Gaussian degradation model

  • Published:2016-04 Issue: Volume:185 Page:64-72
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Pan DonghuiORCID,Liu Jia-BaoORCID,Cao JindeORCID

Funder

National Natural Science Foundation of China

Academic and Technology Leaders to Introduction Projects of Anhui University

Natural Science Foundation for the Higher Education Institutions of Anhui Province of China

National Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference35 articles.

1. Model-based prognostics with concurrent damage progression processes;Daigle;IEEE Trans. Syst. Man Cybern. Syst.,2013

2. Maximum likelihood from incomplete data via the EM algorithm;Dempster;J. R. Stat. Soc. Ser. B,1977

3. Residual life predictions in the absence of prior degradation knowledge;Gebraeel;IEEE Trans. Reliab.,2009

4. Residual-life distributions from component degradation signals;Gebraeel;IIE Trans.,2005

5. Prognostic degradation models for computing and updating residual life distributions in a time-varying environment;Gebraeel;IEEE Trans. Reliab.,2008

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