An ESPRIT-SAA-Based Detection Method for Broken Rotor Bar Fault in Induction Motors

被引:37
|
作者
Xu, Boqiang [1 ]
Sun, Liling [1 ]
Xu, Lie [2 ]
Xu, Guoyi [3 ]
机构
[1] N China Elect Power Univ, Sch Elect Engn, Baoding 071003, Peoples R China
[2] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT9 5AH, Antrim, North Ireland
[3] N China Elect Power Univ, Key Lab Power Syst Protect & Dynam Secur Monitori, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
Broken rotor bar; detection; estimation of signal parameters via rotational invariance technique (ESPRIT); induction motor; simulated annealing algorithm (SAA); PARAMETERS; STATOR;
D O I
10.1109/TEC.2012.2194148
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
This paper presents a novel detection method for broken rotor bar fault (BRB) in induction motors based on the estimation of signal parameters via rotational invariance technique (ESPRIT) and simulated annealing algorithm (SAA). The performance of ESPRIT is tested with the simulated stator current signal of an induction motor with BRB. It shows that even with short-time measurement data, the technique is capable of correctly identifying the frequencies of the BRB characteristic components but with a low accuracy on the amplitudes and initial phases of those components. The SAA is then used to determine their amplitudes and initial phases and shows satisfactory results. Finally, experiments on a 3-kW, 380-V, 50-Hz induction motor are conducted to demonstrate the effectiveness of the ESPRIT-SAA-based method in detecting BRB with short-time measurement data. It proves that the proposed method is a promising choice for BRB detection in induction motors operating with small slip and fluctuant load.
引用
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页码:654 / 660
页数:7
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