A neuro-fuzzy monitoring system - Application to flexible production systems

被引：17
|
作者：
Palluat, N. [1 ]
Racoceanu, D. [1 ]
Zerhouni, N. [1 ]
机构：
[1] Lab Automat Besancon, CNRS, UMR 6596, F-25000 Besancon, France
来源：
COMPUTERS IN INDUSTRY | 2006年 / 57卷 / 06期
关键词：
UML; neural network; neuro-fuzzy; diagnosis; monitoring; maintenance; SCADA; CMMS; FMECA; Fault Tree;
D O I：
10.1016/j.compind.2006.02.013
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The multiple reconfiguration and the complexity of the modem production system lead to design intelligent monitoring aid systems. Accordingly, the use of neuro-fuzzy technics 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. At the end, we illustrate the industrial usefulness of the proposed dynamic neuro-fuzzy monitoring system trough a flexible production system monitoring application. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码：528 / 538
页数：11
相关论文
共 50 条
  • [1] Flexible neuro-fuzzy systems
    Rutkowski, L
    Cpalka, K
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2003, 14 (03): : 554 - 574
  • [2] Neuro-Fuzzy Genetic Algorithms for Monitoring in a Production System
    Djelloul, I.
    Souier, M.
    Sari, Z.
    [J]. 2013 3D INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC), 2013,
  • [3] A neuro-fuzzy application for AC motor drives monitoring system
    Cristaldi, L
    Lazzaroni, M
    Monti, A
    Ponci, F
    [J]. IMTC/O3: PROCEEDINGS OF THE 20TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1 AND 2, 2003, : 1627 - 1632
  • [4] Evolutionary Learning of Flexible Neuro-Fuzzy Systems
    Cpalka, Krzysztof
    Rutkowski, Leszek
    [J]. 2008 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5, 2008, : 969 - 975
  • [5] On designing of flexible neuro-fuzzy systems for classification
    Cpalka, Krzysztof
    Rutkowski, Leszek
    [J]. PROCEEDINGS OF THE 7TH WSEAS INTERNATIONAL CONFERENCE ON SYSTEMS THEORY AND SCIENTIFIC COMPUTATION (ISTACS'07), 2007, : 19 - +
  • [6] A method for designing flexible neuro-fuzzy systems
    Cpalka, Krzysztof
    [J]. ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2006, PROCEEDINGS, 2006, 4029 : 212 - 219
  • [7] A Neuro-Fuzzy Application to Power System
    Haidar, Ahmed M. A.
    Mohamed, Azah
    Jaalam, Norazila
    Khalidin, Zulkeflee
    Kamali, M. S.
    [J]. PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING (IACSIT ICMLC 2009), 2009, : 131 - 135
  • [8] Neuro-fuzzy approach to gear system monitoring
    Wang, W
    Ismail, F
    Golnaraghi, F
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2004, 12 (05) : 710 - 723
  • [9] On Designing of Flexible Neuro-Fuzzy Systems for Nonlinear Modelling
    Cpalka, Krzysztof
    Rebrova, Olga
    Nowicki, Robert
    Rutkowski, Leszek
    [J]. ROUGH SETS, FUZZY SETS, DATA MINING AND GRANULAR COMPUTING, RSFDGRC 2011, 2011, 6743 : 147 - 154
  • [10] On design of flexible neuro-fuzzy systems for nonlinear modelling
    Cpalka, Krzysztof
    Rebrova, Olga
    Nowicki, Robert
    Rutkowski, Leszek
    [J]. INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2013, 42 (06) : 706 - 720
12345