Time-Varying Frequency-Modulated Component Extraction Based on Parameterized Demodulation and Singular Value Decomposition
Time-Varying Frequency-Modulated Component Extraction Based on Parameterized Demodulation and Singular Value Decomposition
复制标题
基于参数化解调和奇异值分解的时变调频分量提取
DOI：
10.1109/tim.2015.2494632
复制
发表时间：
2016-02-01
影响因子：
5.6
通讯作者：
Zhang, Wenming
中科院分区：
文献类型：
--
作者：
Chen, Shiqian;Yang, Yang;Zhang, Wenming
为了分析时变调频（FM）信号中有价值的频率成分，在大多数应用中，成分提取是必要的。考虑到参数化解调（PD）在平稳化FM信号方面的优势，提出了一种基于PD和奇异值分解（PD-SVD）的单分量和多分量信号分量提取方法。通过扩展PD的思想，可以去除感兴趣的FM分量的连续相位函数的时变项，从而产生具有恒定相位的高度自相关分量。然后，通过奇异值分解可以实现从噪声或其它分量中提取目标分量。与现有方法相比，该算法能够分析瞬时频率轨迹交叉的多分量信号，有效提高提取分量的信噪比。将该方法应用于多个数值信号和水轮机转子径向振动信号的分析，结果表明该方法的有效性，具有分析实际调频信号的潜力。
To analyze the valuable frequency component for time-varying frequency-modulated (FM) signals, component extraction is necessary in most applications. Considering the advantage of parameterized demodulation (PD) in transforming FM signals to be stationary, a novel component extraction method based on PD and singular value decomposition (PD-SVD) for both monocomponent and multicomponent signals is proposed. By extending the idea of PD, the time-varying term of the continuous phase function for the interested FM component can be removed, thus resulting in a highly self-correlated component with constant phase. Then, the extraction of the target component from noise or other components can be realized by SVD. Compared with the existing methods, the proposed algorithm is able to analyze the multicomponent signal with crossed instantaneous frequency trajectories and effectively improve the signal-to-noise ratio of the extracted component. The effectiveness of the proposed method is demonstrated by applying it on several numerical signals and the radial vibration signal of a hydroturbine rotor, indicating the potential of analyzing many practical FM signals.