神经网络技术在船舶柴油机故障在线诊断中的应用研究  

作　　者：范金宇[1] 黄加亮[1] 

机构地区：[1]集美大学轮机工程学院,福建厦门361021

出　　处：《中国修船》2006年第6期49-52,共4页China Shiprepair

基　　金：福建省自然科学基金资助项目(A0410024)

摘　　要：文章主要研究基于RBF神经网络理论为数学工具对柴油机故障进行计算机仿真诊断,建立船用柴油机征兆与故障样本集,作为神经网络故障诊断的专家知识库,以实现船用柴油机故障诊断。并对柴油机性能工况的故障在线自动诊断进行探索,以提高故障诊断的及时性和准确率,减少误诊。In this paper, the intelligent diagnosis method is studied to diagnose the faults of marine diesel engine bases on the principle of RBF neural network as the mathematical model. The sample base of symptom and trouble for marine diesel engine is set up as specialist knowledge, trouble-shooting was applied to the trouble diagnosis in marine diesel engine. And an on-line auto-diagnosis system to diagnose the performances and running conditions in marine diesel engine was studied. So it increases timeliness and accuracy of the trouble-shooting to reduce misdiagnosis.

关 键 词：船舶柴油机 在线监测 智能诊断 计算机仿真 

分 类 号：U664.121[交通运输工程—船舶及航道工程] TK418[交通运输工程—船舶与海洋工程]