Gas pipeline failure evaluation method based on a Noisy-OR gate bayesian network

Xin Feng, Jun cheng Jiang, Wen feng Wang

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

We propose a method based on the Noisy-OR gate Bayesian network to address cases of insufficient sample data. First, a fault tree model of gas pipelines was established. Mapping this model to the Bayesian network (BN), the failure probability was 0.074 according to a traditional BN and fault tree analysis (FTA). By applying the Noisy-OR gate to determine the conditional probability of related nodes, the failure probability of the system was 0.058. Compared with FTA and the BN, this approach could more precisely determine minimum cut sets and diagnose risky factors. The combination of the BN and a Noisy-OR gate is an alternative method for evaluating the reliability of gas pipelines, and this approach can provide a relatively realistic analysis in other evaluation fields because it considers other influencing factors. The findings of this study can aid decision-making and prevent accidents from occurring.

Original languageEnglish
Article number104175
JournalJournal of Loss Prevention in the Process Industries
Volume66
DOIs
StatePublished - Jul 2020

Keywords

  • Bayesian network
  • Failure evaluation
  • Gas pipeline
  • Noisy-OR gate Model

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