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

  • Byun, Sungil; 
  • Papaelias, Mayorkinos; 
  • Marquez, Fausto Pedro Garcia; 
  • Lee, Dongik
Citations

WEB OF SCIENCE

22
Citations

SCOPUS

29

초록

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.

키워드

autonomous underwater vehicle; performance analysis; fault-tree analysis; reliability; failure; RELIABILITY-ANALYSIS; BAYESIAN NETWORK; PROCESS SYSTEMS; RISK ANALYSIS; SAFETY ANALYSIS; DIAGNOSIS; FAILURE; STATE; FTA
제목
Fault-Tree-Analysis-Based Health Monitoring for Autonomous Underwater Vehicle
저자
Byun, Sungil; Papaelias, Mayorkinos; Marquez, Fausto Pedro Garcia; Lee, Dongik
DOI
10.3390/jmse10121855
발행일
2022-12
유형
Article
저널명
JOURNAL OF MARINE SCIENCE AND ENGINEERING
권
10
호
12