船舶主海水系统智能状态评估模型  

The Intelligent State Evaluation Model of Marine Main Seawater System

作　　者：刘一帆 曹辉[1] 郑卓 汪旭明[1] LIU Yifan;CAO Hui;ZHENG Zhuo;WANG Xuming(Marine Engineering College,Dalian Maritime University,Dalian 116026,Liaoning,China;Marine Design and Research Institute of China,Shanghai 200011,China)

机构地区：[1]大连海事大学轮机工程学院,辽宁大连116026 [2]中国船舶及海洋工程设计研究院,上海200011

出　　处：《船舶工程》2021年第8期4-9,72,共7页Ship Engineering

基　　金：工信部装函资助项目([2018]473号);2018年度辽宁省普通高等教育本科教学改革研究项目。

摘　　要：随着船舶系统维护方式智能化升级,为提高轮机人员工作效率,实现船舶海水系统的视情维修,基于状态识别与层次分析(AHP)-模糊综合评估(FCE)构建了智能状态评估模型(AHP-FCE)。首先,搭建并验证RBF神经网络状态识别模型,获取连续多期系统状态概率向量;然后,利用多级模糊综合状态评估模型对系统当前状态进行综合评估;最后,基于“育鲲”轮真实数据进行可靠性验证,结果证明该模型的计算结果与实际情况匹配。该模型综合考虑连续多期参数,评估结果更加科学合理,可为其他船舶系统的状态评估提供一种新的应用思路。With the intelligent upgrade of ship system maintenance methods,in order to improve the work efficiency of marine engineers and realize the condition-based maintenance of ship seawater systems,an intelligent status assessment model is constructed based on status recognition and analytic hierarchy(AHP)-fuzzy comprehensive evaluation(FCE)(hereinafter referred to as AHP-FCE method).First,the RBF neural network state recognition model is established and verified to obtain the probability vectors of multiple consecutive periods of system states;then,the AHP-FCE method is used to comprehensively evaluate the current state of the system;finally,reliability verification is carried out based on the real data of M/V Yu Kun.The results prove that the calculation results of the model match the actual situation.In addition,the model comprehensively considers the parameters of multiple consecutive parameters,and the evaluation results are more scientific and reasonable.This model provides a new application idea for the state evaluation of other similar ship systems.

关 键 词：层次分析法 RBF神经网络 模糊综合评估法 状态评估 

分 类 号：U661.43[交通运输工程—船舶及航道工程]