Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

A Temporal Neuro-Fuzzy Monitoring System to Manufacturing Systems

Type de record:

softwarepaper
Créateur:
MahMouMouCho
Éditeur:
arXiv
Hôte:avatar
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. 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

Visit

doi.orgarxiv.org

Tags

Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences

Licenses

arXiv.org perpetual, non-exclusive licensehttp://arxiv.org/licenses/nonexclusive-distrib/1.0/

Similaires

Wind power conversion system model identification using adaptive neuro-fuzzy inference systems: A case studySOLAR RADIATION FORECASTING USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS)ENSEMBLE NEURO-FUZZY BASED SYSTEM FOR VEHICLE THEFT PREDICTION AND RECOVERYAdaptive Neuro-Fuzzy inference system for Egyptian residential construction waste predictionTime Series Prediction of Electricity Demand Using Adaptive Neuro-Fuzzy Inference SystemsNeuro-Fuzzy Adaptive Model Predictive Control for Enhanced Voltage Stability in Transmission Systems

Wind power conversion system model identification using adaptive neuro-fuzzy inference systems: A case study

International audience This study proposes an original adaptive neuro-fuzzy inference

SOLAR RADIATION FORECASTING USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS)

Hybrid intelligent systems have previously been centered on forecasting solar energy using meteorolo

ENSEMBLE NEURO-FUZZY BASED SYSTEM FOR VEHICLE THEFT PREDICTION AND RECOVERY

Vehicle theft is continuously being reported as a global prevalent crime. It often aids the perpetua

Adaptive Neuro-Fuzzy inference system for Egyptian residential construction waste prediction

Construction waste (CW) significantly impacts environmental degradation, resource depletion, and

Time Series Prediction of Electricity Demand Using Adaptive Neuro-Fuzzy Inference Systems

This paper is concerned with the reliable prediction of electricity demands using the Adaptive Neuro

Neuro-Fuzzy Adaptive Model Predictive Control for Enhanced Voltage Stability in Transmission Systems

Abstract Contemporary high-voltage (HV) transmission networks are increasingly str