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