DocumentCode :
530711
Title :
The performance parameter fault diagnosis for automobile engine based on ANFIS
Author :
Kong, Li-Fang ; Wang, Jun ; Wang, Zhong-Hua
Author_Institution :
Basic Depts., Xuzhou Air Force Coll., Xuzhou, China
Volume :
3
fYear :
2010
fDate :
24-26 Aug. 2010
Firstpage :
554
Lastpage :
557
Abstract :
This paper builds the fault diagnosis model and optimizes the input interface of the model by normalizing the initial data of the performance parameter for the automobile engine, carrying on information fusion and adopting the Adaptive Neural Fuzzy Interference System (ANFIS). The recognition rate of the model reaches 94.38% under the test of field test data. Corresponding BP neural network modeling and fuzzy recognition modeling, the model enjoys reliability, strong generalization ability, and high failure recognition rate. Moreover, it can effectively detect the performance parameter failure for the automobile engine.
Keywords :
adaptive systems; automobiles; automotive components; backpropagation; fault diagnosis; fuzzy neural nets; fuzzy reasoning; sensor fusion; ANFIS; BP neural network modeling; adaptive neural fuzzy interference system; automobile engine; failure recognition rate; field test data; fuzzy recognition modeling; information fusion; model input interface; performance parameter fault diagnosis; Automotive engineering; Engines; MATLAB; Mathematical model; Petroleum; ANFIS; Performance Parameter; fault diagnosis; fuzzy recognication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
Type :
conf
DOI :
10.1109/CMCE.2010.5610247
Filename :
5610247
Link To Document :
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