Fault Detection of Electric Motors Application using ML Estimation Method

被引：0
|
作者：
Treetrong, Juggrapong [1 ]
机构：
[1] King Mongkuts Univ Technol North Bangkok, Tech Educ Fac, Dept Teacher Training Mech Engn, Bangkok, Thailand
来源：
MANUFACTURING ENGINEERING AND AUTOMATION II, PTS 1-3 | 2012年 / 591-593卷
关键词：
Signal Processing; Fault Detection; Induction Motors; ML Estimation; Maximization Likelihood Estimation; DIAGNOSIS;
D O I：
10.4028/www.scientific.net/AMR.591-593.1958
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a new method of motor fault detection. ML Estimation is proposed as a key technique for signal processing. The stator current is used data for motor fault analysis. ML Estimation is generally applied to estimate signals for nonlinear model. The expectation is that the method can provide information for fault analysis. The method is tested on 3 different motor conditions: healthy, stator fault, and rotor fault motor at full load condition. Based on experiments, the method can differentiate conditions clearly and be also able to measure fault severity levels.
引用
收藏
页码：1958 / 1961
页数：4
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