压载水系统能过保证船舶在航行过程中船体稳定,是邮轮重要的组成部分。由于压载水系统结构复杂，系统可靠性难以分析。为了分析压载水系统的可靠性变化，考虑系统在连续时间下的状态变化，基于连续贝叶斯网络，建立了一种新的船舶压载水系统可靠性分析方法。首先基于压载水系统的故障机理，提出动态故障树模型。然后利用单位阶跃函数和冲激函数，将动态故障树模型转化为连续时间的贝叶斯网络，对系统可靠性进行分析，最后，利用算例对船舶压载水系统进行仿真，得到船舶压载水系统的可靠性以及剩余寿命随时间变化的曲线。
Ballast water system is an important part of the cruise ship. It can ensure the stability of the ship during navigation. However, the reliability of ballast water system is difficult to analyze because of the complexity of its structure. In order to analyze the reliability of ballast water system, a new reliability analysis method is established based on continuous Bayesian network. This method takes into account the state change of the system under continuous time. Firstly, based on the failure mechanism of ballast water system, a dynamic fault tree model is proposed. Then, using unit step function and impulse function, the dynamic fault tree model is transformed into a continuous time Bayesian network to analyze the system reliability. Finally, the ship ballast water system is simulated using the arithmetic example to obtain the reliability and the curve of remaining life with time.
2023,45(12): 35-39 收稿日期：2022-08-29
DOI：10.3404/j.issn.1672-7619.2023.12.007
分类号：U661.1
作者简介：杨咏(1965-),女,博士,研究员,研究方向为舰船系统优化设计
参考文献：
[1] 杨泽宇, 乔红宇. 基于 InTouch 的船舶压载水监控系统[J]. 中国造船, 2010, 51(3): 185–190
YANG Z Y, Q H Y. Design of ship ballast monitor based on intouch[J]. Shipbuilding of China, 2010, 51(3): 185–190
[2] 张迪, 朱发新, 雷建, 等. 基于模糊故障树的压载水系统可靠性分析[J]. 造船技术, 2012(5): 20–23
[3] 李佩昌, 周海军, 周国敬. 基于专家综合评估的模糊动态故障树分析[J]. 舰船科学技术, 2019, 41(19): 192–197
[4] 白旭, 汤荣铿, 罗小芳, 等. 基于故障树分析和贝叶斯网络方法的半潜式钻井平台系统多状态可靠性分析[J]. 中国造船, 2020, 61(2): 220–228
[5] 易静. 基于贝叶斯网络的舰船故障建模方法研究[J]. 舰船科学技术, 2019, 41(4): 43–45
[6] 苏艳琴, 徐廷学, 张文娟. 粗糙集和贝叶斯网络融合故障诊断方法[J]. 舰船科学技术, 2013, 35(3): 91–93
SU Y Q, XU T X, ZHANG W J. Research on one fusion fault diagnosis method based on rough set theory and bayesian network[J]. Ship Science and Technology, 2013, 35(3): 91–93
[7] 姚成玉, 韩丁丁, 陈东宁, 等. 考虑共因失效的新型连续时间动态贝叶斯网络可靠性分析方法[J]. 仪器仪表学报, 2022, 43(6): 174–184
[8] MAMDIKAR M R, KUMAR V, SINGH P. Dynamic reliability analysis framework using fault tree and dynamic Bayesian network: A case study of NPP[J]. Nuclear Engineering and Technology, 2022, 54(4): 1213–1220
[9] 王晓明, 李彦锋, 李爱峰, 等. 模糊数据下基于连续时间贝叶斯网络的整流回馈系统可靠性建模与评估[J]. 机械工程学报, 2015, 51(14): 167–174
[10] CODETTA-RAITERI D, PORTINALE L. Generalized continuous time bayesian networks as a modelling and analysis formalism for dependable systems[J]. Reliability Engineering & System Safety, 2017, 167: 639–651
[11] 张大信, 郭基联. 动态故障树顶事件概率计算流程[J]. 信息工程大学学报, 2021, 22(5): 566–570+605
[12] LEI X, MACKENZIE C A. Assessing risk in different types of supply chains with a dynamic fault tree[J]. Computers & Industrial Engineering, 2019, 137: 106061
[13] 隆奇芮, 郭智威, 白秀琴, 等. 大型邮轮压载水系统设计技术研究[J]. 舰船科学技术, 2020, 42(5): 85–91
LONG Q R, GUO Z W, BAI X Q, et al. Research on the design technology of ballast water system for large cruise ships[J]. Ship Science and Technology, 2020, 42(5): 85–91
