A novel Bayesian update method for parameter-reconstruction of remaining useful life prognostics

Pengfei Wen, Shaowei Chen, Shuai Zhao, Yong Li, Yan Wang, Zhi Dou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

—Remaining useful life (RUL) prediction is a core component for reliability research and condition-based maintenance (CBM). In the existing parameter-reconstruction method, the degradation trajectory of an in-situ unit is reconstructed by the weighted sum of that of historical units. However, this method requires an optimization problem to be solved for each new measurement, which leads to an excessively consumed time and does not satisfy the requirements of online prognostics and decision-making. In this paper, these weights are assumed as a set of probabilities, based on which they can be updated via Bayesian estimation, instead of solving the optimization problem at each observation epoch. To verify the proposed approach, a data set developed by a commercial simulation tool for aircraft turbofan engines is involved. In light of the implement situation of the proposed approach on this data set, the absolute error of the prognostics result and the consumed time for computation are significantly reduced compared with the existing approach.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538683576
DOIs
StatePublished - Jun 2019
Event2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019 - San Francisco, United States
Duration: 17 Jun 201920 Jun 2019

Publication series

Name2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019

Conference

Conference2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019
Country/TerritoryUnited States
CitySan Francisco
Period17/06/1920/06/19

Keywords

  • -online prognostics
  • Bayesian update
  • Reconstruction
  • RUL estimation

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