Online monitoring and prognostics for passive components in nuclear power plants

Pradeep Ramuhalli, Surajit Roy, Jangbom Chai

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

This paper describes research toward developing prognostics technologies for light water nuclear power reactor components. The focus of this paper is on passive components (those that do not need to change state or move to perform their function), although the technologies are applicable to other classes of components as well. A prototypic failure mechanism (high-cycle fatigue) is used to focus the efforts and provide context for the development effort. A Bayesian framework is proposed for the prognostics of remaining useful life and applied to simulated data sets representing nondestructive measurements of high-cycle fatigue damage. The initial results of the prognostics based on simulated data sets are presented.

Original languageEnglish
Pages (from-to)228-242
Number of pages15
JournalNuclear Science and Engineering
Volume182
Issue number2
DOIs
StatePublished - Feb 2016
Externally publishedYes

Keywords

  • Bayesian prognostics
  • Fatigue crack precursors
  • Online monitoring

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