ON THE INTELLIGENT FAULT DIAGNOSIS METHOD FOR MARINE DIESEL ENGINE

被引:0
|
作者
Li, Peng [1 ]
Su, Baoku [1 ]
机构
[1] Harbin Inst Technol, Harbin 150001, Peoples R China
来源
2008 INTERNATIONAL CONFERENCE ON APPERCEIVING COMPUTING AND INTELLIGENCE ANALYSIS (ICACIA 2008) | 2008年
关键词
Fuzzy neural network; Genetic algorithm; Intelligent fault diagnosis; Marine diesel engine;
D O I
10.1109/ICACIA.2008.4770052
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The marine diesel engine is a complex system. Its mapping process of fault diagnosis has multi-fault attributes, which means input and output of fault pattern attribute are the multi-mapping relations. An approach of intelligent fault diagnosis using fuzzy neural networks and genetic algorithms to optimize and train is studied in this paper for this system. The structure and the model of intelligent fault diagnosis made up of fuzzy neural network were introduced. Its weight and the threshold value optimized and trained by the genetic algorithm are presented. Finally, this fuzzy neural network system optimized and trained by genetic algorithm was applied to the fault diagnosis of the marine diesel engine. The simulation showed feasibility and validity of this method. The precision of fault diagnosis can be improved effectively, and the generation capacity of the intelligent fault diagnosis system and the accurate knowledge expression are enhanced.
引用
收藏
页码:397 / 400
页数:4
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