DocumentCode :
3501007
Title :
Fault Prediction Using Artificial Neural Network and Fuzzy Logic
Author :
Virk, Shafqat M. ; Muhammad, Aslam ; Martinez-Enriquez, A.M.
Author_Institution :
Dept. of CSE, U.E.T., Lahore
fYear :
2008
fDate :
27-31 Oct. 2008
Firstpage :
149
Lastpage :
154
Abstract :
This paper studies different vehicle fault prediction techniques, using artificial neural network and fuzzy logic based model. With increasing demands for efficiency and product quality as well as progressing integration of automatic control systems in high-cost mechatronics and safety-critical processes, monitoring is necessary to detect and diagnose faults using symptoms and related data. However, beyond protective maintenance services, it is viable to integrate fault prediction services. Thus, we studied different parameters to model a fault prediction service. This service not only helps to predict faults but is also useful to take precautionary measures to avoid tangible and intangible losses.
Keywords :
fault diagnosis; fuzzy control; maintenance engineering; neurocontrollers; road safety; road vehicles; artificial neural network; automatic control systems; fuzzy logic; high-cost mechatronics; product quality; protective maintenance services; safety-critical processes; vehicle fault prediction techniques; Artificial neural networks; Automatic control; Computerized monitoring; Fault detection; Fuzzy logic; Loss measurement; Mechatronics; Predictive models; Protection; Vehicles; Artificial Neural Network; Back-propagation; Faults; Fuzzy Logic; Neuro-Fuzzy; Neuro-Neuro; Recurrent Neural Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence, 2008. MICAI '08. Seventh Mexican International Conference on
Conference_Location :
Atizapan de Zaragoza
Print_ISBN :
978-0-7695-3441-1
Type :
conf
DOI :
10.1109/MICAI.2008.38
Filename :
4682457
Link To Document :
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