检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:庄双勇[1] 赵伟[1] 黄松岭[1] Zhuang Shuangyong;Zhao Wei;Huang Songling(State Key Lab of Control and Simulation of Power Systems and Generation Equipment,Department of Electrical Engineering,Tsinghua University,Belting 100084,China)
机构地区:[1]清华大学电机系电力系统及发电设备控制和仿真国家重点实验室
出 处:《仪器仪表学报》2018年第6期73-81,共9页Chinese Journal of Scientific Instrument
基 金:国家高技术研究发展计划(863计划)(2015AA050404)项目资助
摘 要:提出一种压缩感知正交匹配追踪(CS-OMP)超谐波测量新算法,即运用压缩感知理论,通过引入插值系数,基于离散傅里叶变换(DFT)系数向量和狄利克雷核矩阵,构建了高频率分辨率的压缩感知模型,并基于正交匹配追踪算法,在不增加被测数据观测时间前提下,将超谐波测量的频率分辨率提高了一个数量级。数值仿真分析以及两种非线性负荷的实测数据验证的结果表明,该算法可将测得数据频率分辨率由2 k Hz细化为200 Hz,能实现对被测信号中超谐波频率成分的精确定位,也可准确求解出其幅值信息,从而有效地弥补了DFT算法存在的观测时间与频率分辨率互相限制的固有缺陷,在更准确测量超谐波方面展现出良好前景。A novel compressive sensing-orthogonal matching pursuit(CS-OMP) supraharmonics measurement algorithm is proposed.Firstly,the algorithm based on discrete Fourier transform(DFT) coefficient vectors and Dirichlet kernel matrix constructs a higher frequency resolution compressed sensing model by introducing an interpolation coefficient. Then,the sparse spectral of the supraharmonics is reconstructed by using orthogonal matching pursuit algorithm,frequency resolution can be improved by an order-ofmagnitude without extending signal's observation time. Simulation analysis and the verification results of the measured data of the two nonlinear loads show that the proposed algorithm can refine the frequency resolution of the measured data from 2 k Hz to 200 Hz,and the amplitudes of supraharmonics can also be accurately calculated. The new algorithm shows a good prospect in precision measurement of supraharmonics and can overcome the intrinsic deficiencies of DFT,the mutual restriction of observation time and frequency resolution.
关 键 词:电能质量 超谐波 压缩感知 正交匹配追踪 测量算法
分 类 号:TM935.21[电气工程—电力电子与电力传动]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:13.58.45.209