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机构地区:[1]湖南大学电气信息与工程学院,长沙410082
出 处:《电力系统及其自动化学报》2016年第8期74-78,共5页Proceedings of the CSU-EPSA
摘 要:局部均值分解LMD是一种处理非线性、非平稳信号的新方法。但是该算法存在滑动平均步长较难选择、计算速度慢、端点效应等理论问题。为了解决这些问题,提出了一种改进的LMD算法。首先采用支持向量机和镜像延拓相结合的方法将信号端点延拓,再用3次B样条插值求取包络线,最后分解得到乘积函数,并将该方法用于谐波及暂态谐波失真信号的检测中。仿真结果验证了该算法的可行性和有效性。Local mean decomposition (LMD) is a new method to deal with nonlinear, non-stationairy signals, but it has theoretical issues such as difficulty in selecting the moving average step length, slow calculation spee dand end effect. To solve these problems, an improved LMD is presented. First, support vector machine and mirror extension method are combined to extend the signal endpoints, then the envelopes are obtained by cubic B-spline interpolation, and final- ly, product functions are obtained by LMD. The method is used for the detection of harmonic and transient harmonic dis- turbance signals. The simulation results demonstrate that the proposed algorithm is effective and feasible.
关 键 词:局部均值分解 3次B样条插值 支持向量机 镜像延拓 谐波
分 类 号:TM714[电气工程—电力系统及自动化]
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