A Multi-sensor Fusion Scheme for Broken Rotor Bar and Air-gap Eccentricity Detection of Induction Machines

被引：0
|
作者：
Luo, Genyi [1 ]
Habetler, Thomas G. [1 ]
Hurwitz, Jed [2 ]
机构：
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
[2] Analog Devices Inc, Edinburgh, Midlothian, Scotland
来源：
2019 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE) | 2019年
关键词：
Broken rotor bar; eccentricity; fault diagnosis; induction machines; sensor fusion; MOTORS;
D O I：
10.1109/ecce.2019.8912275
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：
A new multi-sensor fusion scheme for induction motor broken rotor bar fault and dynamic air gap eccentricity fault detection is proposed in this paper to refine the sensor selecting process and improve the correlation of data. Instead of combining the signatures for the same fault, the proposed scheme combines the characteristic frequencies from different sensor related to the same abnormal phenomenon such rotor asymmetry and speed ripples. An experimental validation is performed on a 7.5 horsepower induction motor. The data for unbalanced load condition is also gathered, and it can be separated from similar condition. The experimental results validated the new fusion scheme and proved that with the proposed scheme, higher sensitivity and specificity can be achieved.
引用
收藏
页码：3905 / 3911
页数：7
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