The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this metho...The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this method usually estimates L signal DOAs by finding roots that lie closest to the unit circle of a（2M-1）-order polynomial, where L 〈 M. A novel efficient root-MUSIC-based method for direction estimation is presented, in which the order of polynomial is efficiently reduced to 2L. Compared with the unitary root-MUSIC（U-root-MUSIC） approach which involves real-valued computations only in the subspace decomposition stage, both tasks of subspace decomposition and polynomial rooting are implemented with real-valued computations in the new technique,which hence shows a significant efficiency advantage over most state-of-the-art techniques. Numerical simulations are conducted to verify the correctness and efficiency of the new estimator.展开更多
为了实现异步电动机转子断条故障的准确检测,提出了一种基于多重信号分类MUSIC(root multiple signal classification)与普罗尼P rony算法相结合的异步电动机转子断条故障检测新方法。MUSIC方法具有频率分辨力高,所需数据少的特点。首...为了实现异步电动机转子断条故障的准确检测,提出了一种基于多重信号分类MUSIC(root multiple signal classification)与普罗尼P rony算法相结合的异步电动机转子断条故障检测新方法。MUSIC方法具有频率分辨力高,所需数据少的特点。首先利用该方法计算出异步电机转子发生断条故障时的特征分量及其他分量的频率值,进而引入扩展Prony法中的最小二乘法,估计出特征分量及其它分量的幅值和初相角。仿真及实验结果表明,基于MUSIC和Prony算法的异步电动机转子断条故障检测方法切实可行,并且适用于负荷波动、噪声干扰等不利情况。展开更多
基金supported by the National Natural Science Foundation of China(61501142)the Shandong Provincial Natural Science Foundation(ZR2014FQ003)+1 种基金the Special Foundation of China Postdoctoral Science(2016T90289)the China Postdoctoral Science Foundation(2015M571414)
文摘The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this method usually estimates L signal DOAs by finding roots that lie closest to the unit circle of a（2M-1）-order polynomial, where L 〈 M. A novel efficient root-MUSIC-based method for direction estimation is presented, in which the order of polynomial is efficiently reduced to 2L. Compared with the unitary root-MUSIC（U-root-MUSIC） approach which involves real-valued computations only in the subspace decomposition stage, both tasks of subspace decomposition and polynomial rooting are implemented with real-valued computations in the new technique,which hence shows a significant efficiency advantage over most state-of-the-art techniques. Numerical simulations are conducted to verify the correctness and efficiency of the new estimator.
文摘为了实现异步电动机转子断条故障的准确检测,提出了一种基于多重信号分类MUSIC(root multiple signal classification)与普罗尼P rony算法相结合的异步电动机转子断条故障检测新方法。MUSIC方法具有频率分辨力高,所需数据少的特点。首先利用该方法计算出异步电机转子发生断条故障时的特征分量及其他分量的频率值,进而引入扩展Prony法中的最小二乘法,估计出特征分量及其它分量的幅值和初相角。仿真及实验结果表明,基于MUSIC和Prony算法的异步电动机转子断条故障检测方法切实可行,并且适用于负荷波动、噪声干扰等不利情况。
