Intelligent Vibration Signal Diagnostic System Using Artificial Neural Network

被引：1
|
作者：
Lin, Chang-Ching [1 ]
Shieh, Shien-Chii [2 ]
机构：
[1] Tamkang Univ, Grad Inst Management Sci, Tamsui, Taipei County, Taiwan
[2] Tungnan Univ, Dept Ind Engn & Management, Taipei, Taiwan
来源：
ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL I, PROCEEDINGS | 2009年
关键词：
intelligent system; self diagnostic; artificial neural network; vibration signals diagnostic; fault diagnosis; CLASSIFICATION;
D O I：
10.1109/ICICTA.2009.91
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper artificial neural network (ANN) technologies and analytical models have been investigated and incorporated to increase the effectiveness and efficiency of machinery self diagnostic system. Several advanced vibration trending methods have been studied and used to quantify machine operating conditions. An on-line, multi-channel condition monitoring procedure has been developed and coded. The major technique used for self diagnostic is a modified ARTMAP neural network. The objective is to provide a rigid solution for condition-based intelligent self diagnostic system.
引用
收藏
页码：346 / 349
页数：4
相关论文
共 50 条
  • [21] An intelligent sales forecasting system through integration of artificial neural network and fuzzy neural network
    Kuo, RJ
    Xue, KC
    [J]. COMPUTERS IN INDUSTRY, 1998, 37 (01) : 1 - 15
  • [22] Intelligent Autonomous Vehicle Navigated by using Artificial Neural Network
    Mahmud, Firoz
    Arafat, Al
    Zuhori, Syed Tauhid
    [J]. 2012 7TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (ICECE), 2012,
  • [23] Intelligent Sampling for Colombian Soundscapes Using an Artificial Neural Network
    Quiroz, Luis
    Gomez, Jairo
    Agudelo, Oscar
    Tobon, Luis
    [J]. APPLIED COMPUTER SCIENCES IN ENGINEERING, 2017, 742 : 179 - 188
  • [24] Intelligent optical sensors using artificial neural network approach
    Dias, Ireneu
    Oliveira, Rui
    Frazao, Orlando
    [J]. INNOVATION IN MANUFACTURING NETWORKS, 2008, : 289 - 294
  • [25] Intelligent condition monitoring of a gearbox using artificial neural network
    Rafiee, J.
    Arvani, F.
    Harifi, A.
    Sadeghi, M. H.
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (04) : 1746 - 1754
  • [26] Intelligent recognition technology using artificial neural network for graphics
    Fan, Bin
    Zeng, Xiao-Jing
    Zhao, Zhu
    [J]. International Journal of Simulation: Systems, Science and Technology, 2016, 17 (18): : 1 - 7
  • [27] EEG Emotion Signal of Artificial Neural Network by using Capsule Network
    Ali, Usman
    Li, Haifang
    Yao, Rong
    Wang, Qianshan
    Hussain, Waqar
    Duja, Syed Badar Ud
    Amjad, Muhammad
    Ahmed, Bilal
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (01) : 434 - 443
  • [28] Pharyngeal wall vibration detection using an artificial neural network
    K. Behbehani
    F. Lopez
    F. -C. Yen
    E. A. Lucas
    J. R. Burk
    J. P. Axe
    F. Kamangar
    [J]. Medical and Biological Engineering and Computing, 1997, 35 : 193 - 198
  • [29] Pharyngeal wall vibration detection using an artificial neural network
    Behbehani, K
    Lopez, F
    Yem, FC
    Lucas, EA
    Burk, JR
    Axe, JP
    Kamangar, F
    [J]. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 1997, 35 (03) : 193 - 198
  • [30] Training of an artificial neural network in the diagnostic system of a technical object
    Stanisław Duer
    Konrad Zajkowski
    Ireneusz Płocha
    Radosław Duer
    [J]. Neural Computing and Applications, 2013, 22 : 1581 - 1590
12345