负载连续变化时鼠笼电机早期转子断条故障诊断
Fault diagnosis of incipient broken rotor bars for squirrel-cage induction motor under continuous variable load condition
查看参考文献15篇
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文摘
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负载连续变化时,鼠笼电机定子电流表现为非平稳信号,因此基于快速傅里叶变换的电机电流信号特征分析(MCSA)方法难以有效诊断早期转子断条故障。提出了一种负载连续变化时鼠笼电机早期转子断条故障诊断新方法。首先对定子暂态电流作希尔伯特变换以消除基频影响,然后对得到的解析信号包络线作离散小波变换,根据提取到的故障特征频率2sf 演变图谱判断是否发生了转子断条故障,最后结合小波能量给出故障状态定量分析。在3 kW 电机实验台上对所提出的方法进行实验验证,实验结果证实了所提方法的有效性。 |
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其他语种文摘
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Under continuous variable load condition,the stator current of squirrel-cage induction motor is a non-stationary signal,therefore the motor-current-signature analysis (MCSA)method based on fast Fourier transform (FFT)can hardly diagnosis the incipient broken rotor bar defect. This paper proposes a novel fault diagnosis method for the incipient broken rotor bars of squirrel-cage induction motor operating under continuous variable load condition. Firstly,the Hilbert transformation is performed on the stator transient current to eliminate the effect of the fundamental frequency. Then,the discrete wavelet transformation is conducted on the envelope of the obtained analytic signal; and according to the faulty frequency 2sf characteristic pattern,it is judged if the broken rotor bar defect occurs. Finally, combining the wavelet energy techniques,the quantitative analysis of the fault state is given. The experiment verification was performed on a 3kw motor experiment test bench; the experiment results prove the effectiveness of the proposed method. |
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来源
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仪器仪表学报
,2014,35(7):1646-1653 【核心库】
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关键词
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鼠笼电机
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希尔伯特变换
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小波变换
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故障诊断
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地址
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中国科学院沈阳自动化研究所, 中国科学院网络化控制系统重点实验室, 沈阳, 110016
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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0254-3087 |
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学科
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电工技术 |
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基金
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中国科学院重点部署项目
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文献收藏号
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CSCD:5198765
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参考文献 共
15
共1页
|
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1.
阳同光. 混合蛙跳脊波神经网络观测器电机故障诊断研究.
仪器仪表学报,2013,34(1):193-199
|
被引
8
次
|
|
|
|
|
2.
彭宇. 故障预测与健康管理技术综述.
电子测量与仪器学报,2010,24(1):1-9
|
被引
76
次
|
|
|
|
|
3.
Mehrjou M R. Rotor fault condition monitoring techniques for squirrel-cage induction machine-A review.
Mechanical Systems and Signal Processing,2011,25(8):2827-2848
|
被引
15
次
|
|
|
|
|
4.
胡为. 改进的符号时间序列分析方法及其在电机故障诊断中的应用.
仪器仪表学报,2009,30(4):760-766
|
被引
12
次
|
|
|
|
|
5.
谢国民. 采煤机电动机故障诊断专家系统的研究与应用.
信息与控制,2013,42(3):358-363
|
被引
6
次
|
|
|
|
|
6.
祝洪宇. 基于变频器供电侧电流Hilbert 解调制方法的空载电机转子断条故障诊断.
仪器仪表学报,2014,35(1):140-147
|
被引
5
次
|
|
|
|
|
7.
Puche-Panadero R. Improved resolution of the MCSA method via hilbert transform,enabling the diagnosis of rotor asymmetries at very low slip.
IEEE Transactions on Energy Conversion,2009,24(1):52-59
|
被引
8
次
|
|
|
|
|
8.
Kia S H. A high-resolution frequency estimation method for three-phase induction machine fault detection.
IEEE Transactions on Industrial Electronics,2007,54(4):2305-2314
|
被引
9
次
|
|
|
|
|
9.
Thomson W T. Current signature analysis to detect induction motor faults.
Industry Applications Magazine,2001,7(4):26-34
|
被引
4
次
|
|
|
|
|
10.
Jee-Hoon J. Online diagnosis of induction motors using MCSA.
Industrial Electronics,IEEE Transactions on,2006,53(6):1842-1852
|
被引
16
次
|
|
|
|
|
11.
Antonino-Daviu J. Application and optimization of the discrete wavelet transform for the detection of broken rotor bars in induction machines.
Applied and Computational Harmonic Analysis,2006,21(2):268-279
|
被引
4
次
|
|
|
|
|
12.
Zhengping Z. A novel detection method of motor broken rotor bars based on wavelet ridge.
Energy Conversion,IEEE Transactions on,2003,18(3):417-423
|
被引
2
次
|
|
|
|
|
13.
Cusido J. Wavelet and PDD as fault detection techniques.
Electric Power Systems Research,2010,80(8):915-924
|
被引
1
次
|
|
|
|
|
14.
Trzynadlowski A M. Comparative investigation of diagnostic media for induction motors: A case of rotor cage faults.
Industrial Electronics,IEEE Transactions on,2000,47(5):1092-1099
|
被引
5
次
|
|
|
|
|
15.
Mallat S G. A theory for multiresolution signal decomposition: the wavelet representation.
Pattern Analysis and Machine Intelligence,IEEE Transactions on,1989,11(7):674-693
|
被引
1779
次
|
|
|
|
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