Case-based reasoning system with Petri nets for induction motor fault diagnosis

被引：69

作者：

Yang, BS

Jeong, SK

Oh, YM

Tan, ACC

机构：

[1] Pukyong Natl Univ, Sch Mech Engn, Pusan 608739, South Korea

[2] Poscon Corp, Ctr Res & Dev, Seoul, South Korea

[3] Queensland Univ Technol, Sch Mech Mfg & Med Engn, Brisbane, Qld 4001, Australia

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2004年 / 27卷 / 02期

关键词：

case-based reasoning; case retrieval; Petri net; diagnosis; induction motor; maintenance; condition monitoring;

D O I：

10.1016/j.eswa.2004.02.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an innovative approach for integrating case-based reasoning (CBR) with Petri net for the fault diagnosis of induction motors. In the CBR system, maintenance engineers can retrieve the information from previous cases which closely resemble the new problem and solve the new problem using the information from the previous cases. The proposed system has been used in fault diagnosis of electric motor to confirm the system performance. The result shows the proposed system performs better than the conventional CBR system. (C) 2004 Elsevier Ltd. All rights reserved.

引用

页码：301 / 311

页数：11

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