In recent years, Autonomous Underwater Vehicles (AUVs) have rapidly developed as vital tools for marine resource exploration. Ensuring the efficient and reliable performance of AUVs is crucial, especially when subsystems fail or hazardous conditions arise, as this affects their ability to complete missions. This paper focuses on the reliability of AUV’s complex systems and proposes a weighted fuzzy fault tree reasoning mechanism, which can identify the optimal course of action when the AUV is in a critical state or a subsystem failure prevents the completion of its mission. By thoroughly analyzing the AUV’s current overall status, the mechanism determines the best decision-making strategy to maximize the chances of safely recovering the AUV.
Research on Reliability of Underwater Vehicle Based on Weighted Fuzzy Fault Tree
16.05.2025
2527970 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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