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首页> 外文期刊>Journal of Microwaves, Optoelectronics and Electromagnetic Applications >Use of a combined SVD-Kalman filter approach for induction motor broken rotor bars identification
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Use of a combined SVD-Kalman filter approach for induction motor broken rotor bars identification

机译:结合使用SVD-Kalman滤波器方法来识别感应电动机转子条是否损坏

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This paper describes a new parametric spectral estimator for the identification of rotor bar fault of an induction motor by analyzing the stator current. This approach combines two methods: The first one, the Singular Value Decomposition method which allows the accurate detection and location of the fault's signature frequency. The second method allows the estimation of the fault amplitude. To this end, the Kalman filter is used for its efficient estimation of both amplitude and phase using the frequencies obtained by the first method. This combination of both methods gives a better frequency resolution for a very short acquisition time, which cannot be obtained using the conventional method of the Periodogram. Moreover, in order to reduce the significant computation time resulting from the use of the Kalman filter, the proposed approach is applied only to the frequency band where the fault signature is likely to appear. A series of tests will be carried out on real signals representing rotor faults.
机译:本文介绍了一种新的参数频谱估计器,用于通过分析定子电流来识别感应电动机的转子棒故障。这种方法结合了两种方法:第一种是奇异值分解方法,该方法可以精确检测和定位故障的特征频率。第二种方法可以估计故障幅度。为此,卡尔曼滤波器用于使用通过第一种方法获得的频率对幅度和相位进行有效估计。两种方法的这种组合可在非常短的采集时间内提供更好的频率分辨率,这是使用周期图的常规方法无法获得的。而且,为了减少由于使用卡尔曼滤波器而导致的大量计算时间,所提出的方法仅被应用于可能出现故障签名的频带。将对代表转子故障的真实信号进行一系列测试。

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