Dependency model-based multiple fault diagnosis using knowledge of test result and fault prior probability

Xiaofeng Lv, Deyun Zhou, Ling Ma, Yongchuan Tang

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Aiming at solving the multiple fault diagnosis problem as well as the sequence of all the potential multiple faults simultaneously, a new multiple fault diagnosis method based on the dependency model method as well as the knowledge in test results and the prior probability of each fault type is proposed. Firstly, the dependency model of the system can be built and used to formulate the fault-test dependency matrix. Then, the dependency matrix is simplified according to the knowledge in the test results of the system. After that, the logic 'OR' operation is performed on the feature vectors of the fault status in the simplified dependency matrix to formulate the multiple fault dependency matrix. Finally, fault diagnosis is based on the multiple fault dependency matrix and the ranking of each fault type calculated basing on the prior probability of each fault status. An illustrative numerical example and a case study are presented to verify the effectiveness and superiority of the proposed method.

Original languageEnglish
Article number311
JournalApplied Sciences (Switzerland)
Volume9
Issue number2
DOIs
StatePublished - 16 Jan 2019

Keywords

  • Concurrent diagnosis
  • Dependency model
  • Fault prior probability
  • Multiple fault diagnosis
  • Sequential diagnosis

Fingerprint

Dive into the research topics of 'Dependency model-based multiple fault diagnosis using knowledge of test result and fault prior probability'. Together they form a unique fingerprint.

Cite this