Fault detection and isolation in nonlinear dynamic systems: A fuzzy-neural approach

被引：0
|
作者：
Chafi, MS [1 ]
Akbarzadeh-T, MR [1 ]
Moavenian, M [1 ]
机构：
[1] Azad Univ Eslamshahr, Tehran, Iran
来源：
10TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3: MEETING THE GRAND CHALLENGE: MACHINES THAT SERVE PEOPLE | 2001年
关键词：
fault detection and isolation (FDI); CNC milling machine; soft computing; fuzzy decision-making; fuzzy clustering;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel approach based on soft computing concepts is proposed for fault detection and isolation (FDI) of dynamic systems. The proposed method utilizes the concepts of fuzzy clustering, fuzzy decision making and RBF neural networks to create a suitable structure for design of a FDI. The practical applicability is illustrated on a CNC X-axis drive system. Specifically, FDI of twelve different process faults and three different sensor faults is successfully detected for the CNC system.
引用
收藏
页码：1072 / 1075
页数：4
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