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