Title :
The Research of the Intelligent Fault Diagnosis System Optimized by GA for Marine Diesel Engine
Author :
Li, Peng ; Jin, Qi ; Gong, Haixia
Author_Institution :
Postdoctoral for Control Theor. & Control Eng., Harbin Inst. of Technol., Harbin
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.
Keywords :
backpropagation; combustion; convergence; diesel engines; fault diagnosis; fuzzy neural nets; genetic algorithms; marine engineering; marine systems; BP algorithm; convergence performance; fuzzy neural network optimization; genetic algorithm; intelligent fault diagnosis system; marine diesel engine combustion system; marine security; optimization training; Combustion; Convergence; Diesel engines; Fault diagnosis; Fuzzy neural networks; Genetic algorithms; Intelligent networks; Intelligent structures; Intelligent systems; Optimization methods; Fault diagnosis; Fuzzy neural network; Genetic algorithm; Marine diesel engine;
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
DOI :
10.1109/IITA.Workshops.2008.207