Network-based reconfigurable control system design for fault diagnosis

被引:0
|
作者
School of technology, Zhejiang Agricultural and Forestry University, Lin'an, China [1 ]
机构
来源
Intl. J. Adv. Comput. Technolog. | 2012年 / 14卷 / 140-147期
关键词
D O I
10.4156/ijact.vol4.issue14.17
中图分类号
学科分类号
摘要
In order to meet the difference in the production and assembly of equipments as well as the complexity of the fault diagnosis, the network-based reconfigurable mechanical Control System fault diagnosis program was presented. The overall structure and networking schema of distance mechanical fault diagnosis system and the drawback which lies in fault diagnosis system in today's market environment were analyzed, and the distance fault diagnosis network model based on Java EE framework was also described, The inevitability why reconfigurable manufacturing system is brought forth. The structural model and reconfigurable manner of the reconfigurable distance diagnosis system was provided, which used CORBA component technology to achieve reconfiguration. The detail steps of system that take some type of woodworking machinery as diagnosis object was described, and the intelligent diagnosing methods were also researched. The network -based fault diagnosis technology effectively improves the efficiency and accuracy of diagnostic systems.
引用
收藏
相关论文
共 50 条
  • [41] Fault diagnosis of BLDC drive using advanced adaptive network-based fuzzy inference system
    K. V. S. H. Gayatri Sarman
    T. Madhu
    A. Mallikharjuna Prasad
    Soft Computing, 2021, 25 : 12759 - 12774
  • [42] Design of fault diagnosis expert system for electronic control system of adaptive optics based on Fault Tree
    Gao, Guoqing
    Zhou, Luchun
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MECHATRONICS AND INDUSTRIAL INFORMATICS, 2015, 31 : 18 - 22
  • [43] Design of Satellite Network-Based Remote Control and Monitoring System for Power Plants
    Pavarangkoon, Praphan
    Murata, Ken T.
    Inoyama, Yasushi
    Mizuhara, Takamichi
    Kagebayashi, Yuya
    Yamamoto, Kazunori
    Muranaga, Kazuya
    Kimura, Eizen
    2019 IEEE 11TH INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN 2019), 2019, : 621 - 625
  • [44] A Deep Neural Network-Based Feature Fusion for Bearing Fault Diagnosis
    Hoang, Duy Tang
    Tran, Xuan Toa
    Van, Mien
    Kang, Hee Jun
    SENSORS, 2021, 21 (01) : 1 - 13
  • [45] ELM Neural Network-based Fault Diagnosis Method for Mechanical Equipment
    Jia, Chao
    Zhang, Hanwen
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 5257 - 5261
  • [46] Neural network-based analog fault diagnosis using testability analysis
    Barbara Cannas
    Alessandra Fanni
    Stefano Manetti
    Augusto Montisci
    Maria Cristina Piccirilli
    Neural Computing & Applications, 2004, 13 : 288 - 298
  • [47] Development of a network-based signal control system
    Research and Development Center, Development Center's Network Signal Group, East Japan Railway Company
    不详
    Jpn Railw Eng, 2007, 159 (29):
  • [48] Analysis and System Design of Mechanical Fault Diagnosis Based on Deep Neural Network
    Zhao, Keqin
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [49] A neural network-based method for gas turbine blading fault diagnosis
    Angelakis, C.
    Loukis, E.N.
    Pouliezos, A.D.
    Stavrakakis, G.S.
    International Journal of Modelling and Simulation, 2001, 21 (01): : 51 - 60
  • [50] Dynamic neural network-based fault diagnosis of gas turbine engines
    Tayarani-Bathaie, S. Sina
    Vanini, Z. N. Sadough
    Khorasani, K.
    NEUROCOMPUTING, 2014, 125 : 153 - 165