Fault Prediction Using Artificial Neural Network and Fuzzy Logic

• Published in: 2008 Seventh Mexican International Conference on Artificial Intelligence pp. 149 - 154
• Main Authors: Virk, S.M., Muhammad, A., Martinez-Enriquez, A.M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2008
• Subjects: Artificial Neural Network; Artificial neural networks; Automatic control; Back-propagation; Computerized monitoring; Fault detection; Faults; Fuzzy logic; Loss measurement; Mechatronics; Neuro-Fuzzy; Neuro-Neuro; Predictive models; Protection; Recurrent Neural Network; Vehicles
• ISBN: 0769534414; 9780769534411
• DOI: 10.1109/MICAI.2008.38

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.