Title :
Developmentof automobile fault diagnosis expert system based on fault tree — Neural network ensamble
Author :
Youjun, Yue ; Xiang, Li ; Qun, Zong
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
Abstract :
The structure of cars is increasingly complex, the fault type, fault phenomena and fault causes of cars is more complicated, therefore ordinary users are stranded when fault happens. To solve the above questions, this paper outlines a kind of on-vehicle fault diagnosis expert system based on fault tree - neural network ensamble. The knowledge base of the expert system is divided into two parts, the fault tree analysis based knowledge base and neural network ensemble based knowledge base. For the faults easy to form production rules, the fault tree analysis is used to form expert rules. For those difficult to find specific expression between failure mode and fault reason, the neural network ensemble based method is adopt to form a diagnosis model, and it is tested by the simulation examples. Finally, the program language EVC++ under Windows CE is used to develop the fault diagnosis expert system for cars, which had better man-machine interacted interface.
Keywords :
automobiles; automotive engineering; expert systems; fault diagnosis; fault trees; man-machine systems; neural nets; user interfaces; Windows CE; automobile fault diagnosis; cars; expert system; fault tree analysis; knowledge base system; man-machine interface; neural network ensemble; program language EVC++; Biological neural networks; Cognition; Engines; Expert systems; Fault diagnosis; Fault trees; Expert System; fault diagnosis; fault tree; neural network ensamble;
Conference_Titel :
Electronics, Communications and Control (ICECC), 2011 International Conference on
Conference_Location :
Zhejiang
Print_ISBN :
978-1-4577-0320-1
DOI :
10.1109/ICECC.2011.6067801