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
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