DocumentCode :
3501249
Title :
The Performance Parameter Fault Diagnosis for Automobile Engine Based on ANFIS
Author :
Zhang, Jian-Hua ; Kong, Li-Fang ; Tian, Zhang ; Hao, Wei
Author_Institution :
Basic Depts., Xuzhou Air Force Coll., Xuzhou, China
Volume :
2
fYear :
2010
fDate :
23-24 Oct. 2010
Firstpage :
261
Lastpage :
264
Abstract :
In order to solve the fault diagnosis problem of performance Parameter, Adaptive Neuro-Fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine and induce cloud model of fan-out, outputting results are continued. Through verification of the built diagnosis model with data of engine tests, it has been found that the recognition accuracy increase from 84.38% to 98.81%, training error falling from 0.001683 to 0.0011526. Simulation results show that the fitting ability, convergence speed and recognition accuracy of improved ANFIS model are all superior to ANFIS. So a contingent fault of automobile engine can be identified effectively. Moreover, it can effectively detect the performance parameter failure for the automobile engine.
Keywords :
automotive engineering; fault diagnosis; fuzzy neural nets; fuzzy reasoning; internal combustion engines; mechanical engineering computing; ANFIS; adaptive neuro fuzzy inference system; automobile engine; convergence speed; engine test data; fault diagnosis; fitting ability; performance parameter; recognition accuracy; ANFIS; Performance Parameter; cloud model; fault diagnosis; fuzzy recognication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Information Systems and Mining (WISM), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8438-6
Type :
conf
DOI :
10.1109/WISM.2010.149
Filename :
5662400
Link To Document :
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