A Temporal Neuro-Fuzzy Monitoring System to Manufacturing Systems
Abstract
Fault diagnosis and failure prognosis are essential techniques in improving the safety of many manufacturing systems. Therefore, on-line fault detection and isolation is one of the most important tasks in safety-critical and intelligent control systems. Computational intelligence techniques are being investigated as extension of the traditional fault diagnosis methods. This paper discusses the Temporal Neuro-Fuzzy Systems (TNFS) fault diagnosis within an application study of a manufacturing system. The key issues of finding a suitable structure for detecting and isolating ten realistic actuator faults are described. Within this framework, data-processing interactive software of simulation baptized NEFDIAG (NEuro Fuzzy DIAGnosis) version 1.0 is developed. This software devoted primarily to creation, training and test of a classification Neuro-Fuzzy system of industrial process failures. NEFDIAG can be represented like a special type of fuzzy perceptron, with three layers used to classify patterns and failures. The system selected is the workshop of SCIMAT clinker, cement factory in Algeria.
Keywords
Cite
@article{arxiv.1107.3302,
title = {A Temporal Neuro-Fuzzy Monitoring System to Manufacturing Systems},
author = {Rafik Mahdaoui and Leila Hayet Mouss and Mohamed Djamel Mouss and Ouahiba Chouhal},
journal= {arXiv preprint arXiv:1107.3302},
year = {2011}
}
Comments
10 pages, 11 figures, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 3, No. 1, May 2011 ISSN (Online): 1694-0814 www.IJCSI.org