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Identification Of Induction Motor Parameters Using Wiener-Hammerstein Structure Based On Artificial Bee Colony Algorithm

机译:基于人工蜂群算法的Wiener-Hammerstein结构感应电动机参数辨识

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In this paper, identification of parameters of induction motors using the Wiener-Hemerstein structure based on the colony helix algorithm. Identifying the system is actually finding a mathematical model of dynamical systems from input-output data, the results of experiments, and observations. Given the importance of induction machines in the industry, maintaining and protecting them is essential. One of the ways to keep such engines in check is to continuously monitor their health by continuous monitoring of the values of its structural parameters. In this paper, an engine model is estimated using the extracted data from the engine, which includes the effective values of the stator current and the power factor and the application of the colony helium algorithm. The results of the simulation show the high accuracy of the proposed method in identifying the parameters of induction motors in comparison with the previous methods.
机译:本文采用基于菌落螺旋算法的Wiener-Hemerstein结构辨识感应电动机的参数。识别系统实际上是从输入输出数据,实验结果和观察结果中找到动力学系统的数学模型。考虑到感应电机在工业中的重要性,维护和保护它们至关重要。保持这种发动机检查的方法之一是通过连续监视其结构参数的值来连续监视其运行状况。在本文中,使用从发动机提取的数据来估计发动机模型,该数据包括定子电流和功率因数的有效值以及菌落氦算法的应用。仿真结果表明,与以前的方法相比,该方法在识别感应电动机参数方面具有很高的准确性。

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