基于MUSIC与SAA的笼型异步电动机转子断条故障检测

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (709 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract This paper presents a detection method for rotor fault in induction motors, which is based on multiple signal classification(MUSIC) and simulated annealing algorithm(SAA). Firstly, the performance of MUSIC is tested with the simulated stator current signal of an induction motor with broken rotor bar fault. The results show that MUSIC is capable of identifying clearly the frequencies of the broken rotor bar fault feature components and the others in the simulated signal even with short-time sample, although it can not handle with the amplitudes and initial phases of those components. Secondly, SAA is introduced to determine the amplitudes and initial phases of the frequency components in the simulated signal and the results are really satisfactory. Thus paves the way to detect broken rotor bar fault in induction motors by combining MUSIC and SAA. Finally, the related experiment on a 3kW, Y100L—2-typed induction motor is conducted, and the results demonstrate that the MUSIC-SAA-based method to detect broken rotor bar fault in induction motors is effective even with short-time sample, as makes it a promising choice for induction motors operating with fluctuant load or under severe interference.

Key words： Induction motor rotor fault detection MUSIC SAA

Received: 21 April 2011 Published: 20 March 2014

PACS:

TM307

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Sun Liling
	Xu Boqiang
	Li Zhiyuang

Cite this article:

Sun Liling,Xu Boqiang,Li Zhiyuang. A MUSIC-SAA-Based Detection Method For Broken Rotor Bar Fault in Induction Motors[J]. Transactions of China Electrotechnical Society, 2012, 27(12): 205-212.

URL:

http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2012/V27/I12/205

[1] Deleroi W. Broken bar in squirrel cage rotor of an induction motor, part 1: description by superimposed fault currents[J]. Archiv Für Elektrotechnik, 1984, 67: 91-99.
[2] 马宏忠, 胡虔生, 黄允凯, 等. 感应电机转子绕组故障仿真与实验研究[J]. 中国电机工程学报, 2003, 23(4): 107-112.
Ma Hongzhong, Hu Qiansheng, Huang Yunkai, et al. Simulating and experiment studying on rotor winding fault of induction motor[J]. Proceedings of the CSEE, 2003, 23(4): 107-112.
[3] 姜建国, 汪庆生, 杨秉寿, 等. 用自适应方法提取鼠笼式异步电机转子断条的特征分量[J]. 电工技术学报, 1996, 11(4): 176-179.
Jiang Jianguo, Wang Qingsheng, Yang Bingshou, et al. Applying the adaptive noise cancellation to extract the features of squirrel cage induction motor with rotor defects[J]. Transactions of China Electrotechnical Society, 1996, 11(4): 176-179.
[4] 许伯强, 李和明, 孙丽玲, 等. 笼型异步电动机转子断条故障检测新方法[J]. 中国电机工程学报, 2004, 24(5): 115-119.
Xu Boqiang, Li Heming, Sun Liling, et al. A novel detection method for broken rotor bars in induction motors[J]. Proceedings of the CSEE, 2004, 24(5): 115-119.
[5] Liu Zhenxing, Yin Xianggen, Zhang Zhe, et al. Online rotor mixed fault diagnosis way based on spectrum analysis of instantaneous power in squirrel cage induction motors[J]. IEEE Transactions on Energy Conversion, 2004, 19(3): 485-490.
[6] M’hamed Drif, Marques Cardoso A J. The use of the instantaneous-reactive-power signature analysis for rotor-cage-fault diagnostics in three-phase induction motors[J]. IEEE Transactions on Industrial Electronics, 2009, 56(11): 4606-490.
[7] M’hamed Drif, Marques Cardoso A J. Rotor cage fault diagnostics in three-phase induction motors, by the instantaneous phase-angle signature analysis[C]. The Proceedings of IEEE International Symposium on Industrial Electronics, 2007: 1050-1055.
[8] M’hamed Drif, Marques Cardoso A J. The instantaneous power factor approach for rotor cage faults diagnosis in three-phase induction motors[C]. The Proceedings of International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 2008: 173-178.
[9] Czeslaw T Kowalski, Waldemar Kanior. Effectiveness of the frequency analysis of the stator current in the rotor fault detection[C]. The Proceedings of IEEE International Conference on Industrial Technology, 2008: 1-5.
[10] Manés F Cabanas, Francisco Pedrayes, Manuel G Melero, et al. Unambiguous detection of broken bars in asynchronous motors by means of a flux measurement-based procedure[J]. IEEE Transactions on Instrumentation and Measurement, 2011, 60(3): 891-899.
[11] Ahcène Bouzida, Omar Touhami, Rachid Ibtiouen, et al. Fault diagnosis in industrial induction machines through discrete wavelet transform[J]. IEEE Transactions on Industrial Electronics, 2011, 58(9): 4385-4395.
[12] Byunghwan Kim, Kwanghwan Lee, Jinkyu Yang, et al. Automated detection of rotor faults for inverter-fed induction machines under standstill conditions[J]. IEEE Transactions on Industry Applications, 2011, 47(1): 55-64.
[13] 张贤达. 现代信号处理[M]. 北京: 清华大学出版社, 2002.
[14] Luis A Pereira, Denis Fernandes, Daniel S Gazzana, et al. Application of the welch, burg and MUSIC methods to the detection of rotor cage faults of induction motors[C]. The Proceedings of Transmission & Distribution Conference and Exposition: Latin America, 2006: 1-6.
[15] Luis A Pereira, Denis Fernandes, Daniel S Gazzana, et al. Performance evaluation of nonparametric, parametric, and the MUSIC methods to detection of rotor cage faults of induction motors[C]. The Proceedings of IEEE 32nd Industrial Electronics Annual Conference, 2006: 5005-5010.
[16] Shahin Hedayati Kia, Humberto Henao, Gérard André Capolino. A high-resolution frequency estimation method for three-phase induction machine fault[J]. IEEE Transactions on Industrial Electronics, 2007, 54(4): 2305-2314.
[17] 方芳, 杨士元, 侯新国. 基于改进多信号分类法的异步电机转子故障特征分量的提取[J]. 中国电机工程学报, 2007, 27(30): 72-76.
Fang Fang, Yang Shiyuan, Hou Xinguo. Rotor fault feature extraction of motor faults of induction motor based on a modified MUSIC method[J]. Proceedings of the CSEE, 2007, 27(30): 72-76.
[18] 许伯强, 孙丽玲, 李和明. 笼型异步电动机转子断条数目诊断新判据[J]. 中国电机工程学报, 2009, 29(6): 105-110.
Xu Boqiang, Sun Liling, Li Heming. A novel diagnosis criterion for broken rotor bars in induction motors[J]. Proceedings of the CSEE, 2009, 29(9): 105-110.
[19] Stoica P, Nehorai A. MUSIC, maximum likelihood, and Cramer-Rao bound: further results and comparisons[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990, 38(12): 2140-2150.
[20] 徐凌. 智能优化算法及其应用[M]. 北京: 清华大学出版社, 2001.
[21] 章勇高, 将有缘, 方华松, 等. 基于模拟退火算法的共模电磁干扰抑制技术[J]. 电工技术学报, 2008, 23(6): 1-6.
Zhang Yonggao, Jiang Youyuan, Fang Huasong, et al. Common mode EMI suppression based on simulate annealing algorithm[J]. Transactions of China Electrotechnical Society, 2008, 23(6): 1-6.