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arXiv · 1107.3302

A Temporal Neuro-Fuzzy Monitoring System to Manufacturing Systems

Rafik Mahdaoui·Leila Hayet Mouss·Mohamed Djamel Mouss·Ouahiba Chouhal
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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.

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Rafik Mahdaoui, Leila Hayet Mouss, Mohamed Djamel Mouss, Ouahiba Chouhal. 2011-07-17. A Temporal Neuro-Fuzzy Monitoring System to Manufacturing Systems. https://arxiv.org/abs/1107.3302

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