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Remaining storage life prediction for an electromagnetic relay by a particle filtering-based method

  • Youhu Zhao
  • , Enrico Zio
  • , Guicui Fu*
  • *Corresponding author for this work
  • Beihang University

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose a particle filtering-based method for predicting the remaining storage life (RSL) of electromagnetic relays. The RSL prediction problem here addressed has the following three distinctive features: i) limited measurement data available; ii) incomplete run-to-failure data; and iii) no model available for the physical degradation process. Then, to develop the method for RSL prediction, storage testing and degradation mechanism analysis have been carried out to obtain the knowledge and information needed to develop the physical model that supports the RSL prediction procedure. We discuss the three main steps of the proposed prediction method: parameter estimation, model validation and RSL prediction. Data from nine relays are used for estimating the initial parameter values distribution and data from one relay are used for RSL prediction. The RSL prediction results are compared with those obtained by a nonlinear curve-fitting method and a basic particle filtering algorithm. The comparison shows that the proposed method is more effective in predicting the RSL than the other methods.

Original languageEnglish
Pages (from-to)221-230
Number of pages10
JournalMicroelectronics Reliability
Volume79
DOIs
StatePublished - Dec 2017

Keywords

  • Electromagnetic relay
  • Particle filtering
  • Remaining storage life

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