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机构地区:[1]国电南京自动化股份有限公司,南京210032 [2]中州大学,郑州450044
出 处:《微特电机》2014年第11期25-28,39,共5页Small & Special Electrical Machines
基 金:河南省教育厅科技攻关项目(14B470015);郑州市普通科技攻关项目(131PPTGG421-1)
摘 要:提出了一种基于局部特征尺度分解(LCD)的同步电机参数辨识新方法。该方法根据LCD可将同步电机突然短路分解为系列内禀尺度分量(ISC)之和,而且ISC按频率从高到低的顺序依次排列的特点,通过选择不同的ISC分量构造具有自适应能力的滤波器以滤除噪声、获取直流成分和基波电流。对获取的直流电流和基波电流分别运用改进稳健回归算法和Prony算法精确辨识同步电机参数。仿真信号结果表明,与基于EMD的突然短路电流分离方法相比,LCD的分解速度更快;与Prony算法相比,LCD联合Prony的辨识方法受噪声影响小,参数辨识精度高。试验结果进一步验证了所提方法的可行性和正确性。A new method for synchronous motor parameter identification based on local characteristic scale decomposi-tion(LCD) was presented. Short-circuit current was decomposed into the sum of series ISC component, which were ar-ranged in descending order of frequency. The DC component and fundamental current were obtained by selecting differentISC components. The article identified direct current and fundamental current respectively through improved robust regres-sion and Prony algorithm to get synchronous motor parameters. Signal Simulation results show that, compared with the sepa-ration method based on EMD, the method based on LCD is faster. Compared with the Prony algorithm, LCD joint Prony'sidentification little affects by noise and precision parameter identification is high. Experimental result further demonstratesthe feasibility and correctness of the proposed method.
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