Fault-Tree-Analysis-Based Health Monitoring for Autonomous Underwater Vehicle

Sungil Byun, Mayorkinos Papaelias, Fausto Pedro García Márquez, Dongik Lee

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Undersea terrain and resource exploration missions using autonomous underwater vehicles (AUVs) require a great deal of time. Therefore, it is necessary to monitor the state of the AUV in real time during the mission. In this paper, we propose an online health-monitoring method for AUVs using fault-tree analysis. The entire system is divided into four subsystems. Fault trees of each subsystem are designed based on the information of performance and reliability. Using the given subsystem fault trees, the health status of the entire system is evaluated by considering the performance, reliability, fault status, and weight factors of the parts. The effectiveness of the proposed method is demonstrated through simulations with various scenarios.

Original languageEnglish
Article number1855
JournalJournal of Marine Science and Engineering
Issue number12
StatePublished - Dec 2022


  • autonomous underwater vehicle
  • failure
  • fault-tree analysis
  • performance analysis
  • reliability


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