Smart Sensor-Based Synergistic Analysis for Rotor Bar Fault Detection of Induction Motors

被引:42
|
作者
Luong, Peter [1 ]
Wang, Wilson [2 ]
机构
[1] Lakehead Univ, Dept Elect & Comp Engn, Thunder Bay, ON P7B 5E1, Canada
[2] Lakehead Univ, Dept Mech Engn, Thunder Bay, ON P7B 5E1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Broken rotor bars; fault detection; induction motors (IM); smart vibration sensors; smart current sensors; wireless communication; motor current signature analysis (MCSA); RELIABLE DETECTION; ELECTRICAL MOTORS; FREQUENCY; DIAGNOSIS; SIGNAL;
D O I
10.1109/TMECH.2020.2970274
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reliable induction motor (IM) fault detection techniques are very useful in industries to diagnose IM defects and improve operational performance. A smart sensor-based technology is proposed in this article to synergistically use vibration and current harmonics for rotor bar fault detection in IMs. The vibration signal is used for analysis of shaft speed variations and the current harmonics information is applied for rotor bar fault detection. A wireless smart sensor network is developed and used for data collection, allowing for low-cost, low space footprint, and noninvasive installation. The effectiveness of the proposed synergistic technique is examined experimentally, with results demonstrating advantages over conventional methods in terms of accurately differentiating between a healthy and faulty motor, as well as estimating the fault severity, even under zero-load IM conditions. A means to quantify the fault states as diagnostic indices is also proposed for online IM health condition monitoring.
引用
收藏
页码:1067 / 1075
页数:9
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