全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于MUSIC与SAA的笼型异步电动机转子断条故障检测

, PP. 205-212

Keywords: 异步电动机,转子故障,检测,多重信号分类,模拟退火算法

Full-Text   Cite this paper   Add to My Lib

Abstract:

提出了一种基于多重信号分类(MultipleSignalClassification,MUSIC)与模拟退火算法(SimulatedAnnealingAlgorithm,SAA)的异步电动机转子断条故障检测新方法。首先以转子断条故障仿真信号检验MUSIC性能,结果表明MUSIC对于短时信号具备高频率分辨力,可以准确计算转子断条故障特征分量以及其他分量之频率;但对诸频率分量幅值、初相角,MUSIC无能为力。为此,引入SAA确定诸频率分量幅值、初相角,效果理想。进而,对一台Y100L—2型3kW笼型异步电动机完成了转子断条故障检测实验。实验结果表明基于MUSIC与SAA的异步电动机转子断条故障检测方法是切实可行的,并且因仅需处理短时信号而适用于负荷波动、噪声等干扰严重情况。

References

[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.
[3]  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.
[4]  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.
[5]  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.
[6]  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.
[7]  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.
[8]  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.
[9]  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.
[10]  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.
[11]  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.
[12]  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.
[13]  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.
[14]  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.
[15]  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.
[16]  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.
[17]  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.
[18]  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.
[19]  徐凌. 智能优化算法及其应用[M]. 北京: 清华大学出版社, 2001.
[20]  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.
[21]  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.
[22]  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.
[23]  张贤达. 现代信号处理[M]. 北京: 清华大学出版社, 2002.
[24]  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.
[25]  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.
[26]  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.
[27]  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.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133