Health condition estimation of spacecraft key components using belief rule base

Xilang Tang, Xueqi Wang, Mingqing Xiao, Kai Leung Yung, Bin Hu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

This paper proposes a method for estimating the health status of spacecraft key components based on the belief rule base (BRB), a semi-quantitative method which uses both human judgmental information and numerical data. It not only allows experts to establish rules to provide useful conclusions, but also allows historical data to train its parameters to obtain more accurate outputs. To balance the parameter training and experts’ knowledge, the Markov Chain Monte Carlo (MCMC) technique instead of traditional optimization method is used to adjust the BRB parameter. A practical case of estimating the health condition of space application batteries is studied.

Original languageEnglish
Pages (from-to)1107-1127
Number of pages21
JournalEnterprise Information Systems
Volume15
Issue number8
DOIs
Publication statusPublished - 2021

Keywords

  • belief rule base
  • health condition estimation
  • Markov Chain Monte Carlo
  • Spacecraft

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems and Management

Cite this