Switch fault diagnosis of PM brushless DC motor drive using adaptive fuzzy techniques

被引：14

作者：

Awadallah, MA ^{[1
]}

Morcos, MM ^{[1
]}

机构：

[1] Kansas State Univ, Manhattan, KS 66506 USA

来源：

IEEE TRANSACTIONS ON ENERGY CONVERSION | 2004年 / 19卷 / 01期

关键词：

adaptive neuro-fuzzy; machine fault diagnosis;

D O I：

10.1109/TEC.2004.824213

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

An adaptive neuro-fuzzy inference system (ANFIS) is developed to diagnose open switch faults of PM brushless dc motor drives. Features extracted under healthy and faulty operations; using wavelet transform are used to train ANFIS. Testing of the proposed diagnostic system shows it could not only diagnose the fault but identify the faulty switch as well. Good agreement between experimentation and simulation is obtained.

引用

页码：226 / 227

页数：2

共 4 条

[1] Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis [J].