Title :
Monitoring Approach Using Recurrent Radial Basis Function Neural Networks and Neuro-Fuzzy Systems
Author :
Racoceanu, Daniel ; Zerhouni, Noureddine
Author_Institution :
Dept. of Sci., Franche-Comte Univ., Besancon
Abstract :
Multiple reconfiguration and complexity of modern production systems lead to design intelligent monitoring aid systems. The use of artificial intelligence techniques in order to exploit their learning and human experience modeling seems very promising. In this paper, we propose a new monitoring aid system composed by a dynamic neural network detection tool and a neuro-fuzzy diagnosis tool. Learning capabilities due to the neural structure permit us to update the monitoring aid system. The neuro-fuzzy network provides an abductive diagnosis. Moreover it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause
Keywords :
computerised monitoring; production engineering computing; radial basis function networks; recurrent neural nets; abductive diagnosis; artificial intelligence techniques; dynamic neural network detection tool; intelligent monitoring aid systems; modern production systems; neuro-fuzzy diagnosis tool; recurrent radial basis function neural networks; Artificial intelligence; Artificial neural networks; Fuzzy neural networks; Humans; Intelligent systems; Learning; Monitoring; Production systems; Radial basis function networks; Uncertainty;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614721