SACoSaMP在电能质量数据重构中的应用  

Application of SACoSaMP in Power Quality Data Reconstruction

作　　者：肖儿良[1] 朱刚 XIAO Er-Liang;ZHU Gang(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology, Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《控制工程》2019年第1期80-86,共7页Control Engineering of China

基　　金：国家自然科学基金(No.41075019)

摘　　要：为了解决电能质量信号的稀疏度未知和重构性能差的问题,提出采用稀疏度自适应压缩采样匹配追踪(SACoSaMP)算法应用于电能质量数据重构。SACoSaMP算法结合压缩采样匹配追踪(CoSaMP)算法抗干扰能力强和稀疏度自适应匹配追踪(SAMP)算法稀疏度自适应的优点。首先对信号进行稀疏度初始估计,然后在CoSaMP算法框架下进行稀疏度逐步增大的递归运算,以残差值比较为终止条件实现稀疏度自适应。最后采用重构信噪比、均方差误差百分比和能量恢复系数作为评价参数,比较在稀疏基和观测矩阵相同的情况下OMP、CoSaMP、SAMP和SACoSaMP算法的重构效果,仿真实验表明,SACoSaMP算法能量恢复系数高,重构信噪比高,均方误差小,同时具备稀疏度自适应的优点,为电能质量扰动信号数据重构提供了一种新的方向。In order to solve the question that the sparsity of the power quality signal is unknown and the reconstruction performance is poor,this paper proposes a reconstruction method that the sparsity adaptive compressive sampling matching pursuit algorithm(SACoSaMP) is applied for the power quality data reconstruction.SACoSaMP combines the advantages of stronger anti-interference ability of the compressive sampling matching pursuit algorithm and adaptive sparse degrees of the sparsity adaptive matching pursuit algorithm.First of all,the signal sparse degree is initially estimated,and then the sparse degree gradually increases under the CoSaMP algorithm framework of recursive computation,with the comparison of residual value for the termination condition to implement adaptive sparse degrees.Finally,the reconfiguration signal-to-noise ratio,the mean square error percentage and the energy recovery coefficient are used as evaluation parameters.Effects of reconstruction algorithms OMP,CoSaMP,SAMP and SACoSaMP are compared under the same condition of sparse matrix and observation.According to the simulation results,SACoSaMP algorithm not only has a higher energy recovery coefficient,but also has a better signal-to-noise ratio of reconfiguration,and a smaller mean square error,Meanwhile,it has an advantage of adaptive sparse degree,which provides a new direction for data reconfiguration of the power quality disturbance signal.

关 键 词：压缩感知 电能质量 匹配追踪 重构算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]