电能质量信号重构的广义–正则化正交匹配追踪算法
A Generalized-Regularized Orthogonal Matching Pursuit Algorithm for Power Quality Signal Reconstruction
DOI: 10.12677/SG.2019.92006, PDF,    科研立项经费支持
作者: 韩炳辉, 江 辉, 孙兴盛：深圳大学光电工程学院，广东 深圳；彭建春：深圳大学机电与控制工程学院，广东 深圳
关键词: 压缩感知；电能质量；信号重构；正交匹配追踪算法；Compressed Sensing； Power Quality； Signal Reconstruction； Orthogonal Matching Pursuit Algorithm
摘要: 提出了一种基于压缩感知理论的广义–正则化正交匹配追踪(GROMP)算法、并用于电能质量信号重构。这种GROMP算法先基于广义正交匹配追踪算法选择原子并形成原始支撑集，再增加正则化方法对原始支撑集进行二次挑选形成最终支撑集，然后借助最小二乘法更新残差、重构出原信号。它既弥补了广义正交匹配追踪算法精度较低的不足，又克服了正则化正交匹配追踪算法稳定性差和计算量大的缺点。对暂态和稳态电能质量信号重构的仿真结果表明，新的GROMP算法对多种测量矩阵的适应度好。与传统的广义正交匹配追踪算法和正则化正交匹配追踪算法相比，这种新的GROMP算法不仅对各种电能质量信号重构的精度高，而且在压缩比较小时稳定性好。
Abstract: A generalized-regularized orthogonal matching pursuit (GROMP) algorithm is proposed based on compressed sensing theory, and it is used for power quality signal reconstruction. Firstly, the GROMP algorithm selects atoms based on the generalized orthogonal matching pursuit algorithm to form the original support set. Then, the regularization method is added to select atoms from original support set to form the final support set. At last, the least square method is employed to update the residual and reconstruct the original signal. The proposed GROMP algorithm not only compensates for the low accuracy of the generalized orthogonal matching pursuit algorithm, but also overcomes the disadvantages of the poor stability and large computational complexity of the regularized orthogonal matching pursuit algorithm. The simulation results of transient and steady-state power quality signal reconstruction show that the newly proposed GROMP algorithm has good adaptability to a variety of measurement matrices. Compared with the traditional gener-alized orthogonal matching pursuit algorithm and the regularized orthogonal matching pursuit algorithm, the new GROMP algorithm has high reconstruction accuracy for various power quality signals and good stability under small compression ratio.
文章引用：韩炳辉, 江辉, 孙兴盛, 彭建春. 电能质量信号重构的广义–正则化正交匹配追踪算法[J]. 智能电网, 2019, 9(2): 49-60. https://doi.org/10.12677/SG.2019.92006

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