Detection based on ESPRIT and Duffing system for broken rotor bar fault in cage induction motors

被引：0
|
作者：
Xu B. [1 ]
Sun L. [1 ]
机构：
[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2020年 / 40卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Broken rotor bar fault; Detection; Duffing system; ESPRIT; Induction motor; MCSA;
D O I：
10.16081/j.epae.202001026
中图分类号：
学科分类号：
摘要：
When ESPRIT(Estimation of Signal Parameters via Rotational Invariance Technique) is used in the detection of BRBF(Broken Rotor Bar Fault) in cage induction motors, its spectrum analysis results may include some false frequency components that do not exist actually, thus affecting the detection effect. Ai-ming at this problem, the spectrum analysis of stator current signal is carried out by ESPRIT to obtain the frequency components of stator current signal, the false frequency components of which are then identified by Duffing system and eliminated to ensure that the detection of BRBF is effective. The simulative and experimental results validate the effectiveness of the proposed method. © 2020, Electric Power Automation Equipment Press. All right reserved.
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页码：117 / 122
页数：5
相关论文
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