Fault Prediction Using Artificial Neural Network and Fuzzy Logic

被引:9
|
作者
Virk, Shafqat M. [1 ]
Muhammad, Aslam [1 ]
Martinez-Enriquez, A. M. [2 ]
机构
[1] UET, Dept CSE, Lahore, Pakistan
[2] CINVESTAV IPN, Dept CS, Mexico City, DF, Mexico
来源
PROCEEDINGS OF THE SPECIAL SESSION OF THE SEVENTH MEXICAN INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE - MICAI 2008 | 2008年
关键词
Faults; Artificial Neural Network; Fuzzy Logic; Neuro-Fuzzy; Neuro-Neuro; Recurrent Neural Network; Back-propagation;
D O I
10.1109/MICAI.2008.38
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:149 / +
页数:2
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