Reliability analysis based on dynamic Bayesian networks: A case study of an unmanned surface vessel

被引：40

作者：

Gao, Chao ^{[1
]}

Guo, Yongjin ^{[1
]}

Zhong, Mingjun ^{[2
]}

Liang, Xiaofeng ^{[1
]}

Wang, Hongdong ^{[1
]}

Yi, Hong ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, MOE Key Lab Marine Intelligent Equipment & Syst, Shanghai, Peoples R China

[2] Nucl Power Inst China, Sci & Technol Reactor Syst Design Technol Lab, Chengdu, Peoples R China

来源：

OCEAN ENGINEERING | 2021年 / 240卷

基金：

中国国家自然科学基金;

关键词：

Unmanned surface vessel; Dynamic Bayesian network; Dynamic fault tree; Reliability evaluation; Sensitivity analysis; BLOCK DIAGRAM; COMMON-CAUSE; FAULT-TREES; SYSTEMS; MODELS;

D O I：

10.1016/j.oceaneng.2021.109970

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

Unmanned surface vessels (USVs) have been widely used in various activities to date. Reliability is particularly significant for USVs because of the increasing complexity of USV tasks and their characteristic that cannot be repaired during task execution. This study aims to analyse the reliability of USVs' overall system for providing an optimisation reference for their reliability improvement in the design phase. The method for modelling and analysing the reliability of complex systems based on Dynamic Bayesian Networks (DBNs) is studied. The reliability of a USV for seafloor topography survey is analysed. The reliability model of the USV overall system is established by mapping the Dynamic Fault Trees (DFTs) into DBNs considering the system logical structure, redundant configuration and dynamic behaviour. Reliability analysis, including reliability evaluation, importance measure and sensitivity analysis, are conducted on the basis of DBN inference. The overall reliability parameters of the USV are obtained to determine the critical subsystem and components. This research may provide a reference for the reliability design and optimisation of USVs.

引用

页数：14

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