Motor fault diagnosis based on rough sets theory

被引：0
|
作者：
Qiu, CD [1 ]
Ren, GA [1 ]
Tan, Y [1 ]
Di, DH [1 ]
机构：
[1] Dalian Maritime Univ, Dalian 116026, Peoples R China
来源：
ICEMI 2005: CONFERENCE PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL 8 | 2005年
关键词：
fault diagnosis; rough sets theory; Kohonen neural networks; motor;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper introduces a hybrid method of motor online fault diagnosis based on rough set theory and artificial neural networks. The hybrid method doesn't lie on motor mechanism parameter and slip, and doesn't demand adequate motor fault operation data, so that the diagnosis device is common for various type motor. Owing to common of diagnosis device, the hybrid method provides valid support for internet-based motor online condition monitor and fault diagnosis in factory. In this paper, those classified data was measured in laboratory when motor operated in man-made fault. By simulating in MATLAB, and confirm the method is feasible.
引用
收藏
页码：347 / 353
页数：7
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