NDLI: The Research of the Intelligent Fault Diagnosis System Optimized by GA for Marine Diesel Engine

Content Provider	IEEE Xplore Digital Library
Author	Peng Li Qi Jin Haixia Gong
Copyright Year	2008
Description	Author affiliation: Autom. Coll., Harbin Eng. Univ., Harbin (Qi Jin) \|\| Postdoctoral for Control Theor. & Control Eng., Harbin Inst. of Technol., Harbin (Peng Li; Haixia Gong)
Abstract	The marine diesel engine is a complex system, which has the important function to guarantee the marine security. There is strong coupling relationship among the mapping process of fault diagnosis. An approach of intelligent fault diagnosis based on fuzzy neural network optimized and trained by the genetic algorithm (GA) was proposed in this paper for this system. The structure and the parameters of intelligent fault diagnosis system made up of fuzzy neural network were introduced. Through applying the genetic optimization algorithm to its weight and the threshold value that carried by the optimization training, this method may effectively show quick convergence performance. The precision of fault diagnosis also can be improved effectively. Finally this fuzzy neural network system optimized and trained by genetic algorithm was applied in the fault diagnosis of the marine diesel engine's combustion system. The simulation showed feasibility and validity of this method.
Starting Page	263
Ending Page	266
File Size	253926
Page Count	4
File Format	PDF
ISBN	9780769535050
DOI	10.1109/IITA.Workshops.2008.207
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization methods Combustion Intelligent structures Genetic algorithms Convergence Fault diagnosis Intelligent networks Marine diesel engine Diesel engines Genetic algorithm Fuzzy neural networks Fuzzy neural network Intelligent systems
Content Type	Text
Resource Type	Article

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