利用形态非抽样小波的电能质量扰动定位方法  

Power Quality Disturbance Location Method Utilizing Morphological Undecimated Wavelet

作　　者：赵静[1] 何正友[1] 贾勇[1] 钱清泉[1] 

机构地区：[1]西南交通大学电气工程学院,四川省成都市610031

出　　处：《中国电机工程学报》2009年第31期109-114,共6页Proceedings of the CSEE

基　　金：国家自然科学基金项目(50877068);教育部新世纪优秀人才支持计划项目(NCET-06-0799);四川省杰出青年基金项目(06ZQ026-012)~~

摘　　要：由于电能质量扰动信号的波形具有不规则性与多变性,使得目前缺乏成熟的方法对其进行检测与定位。基于此,提出一种新的形态非抽样小波,并将其应用于电能质量扰动信号的检测定位。该形态小波包含了开闭与闭开组合滤波器与可检测突变信号上下边缘的形态梯度,满足信号重构条件。利用Matlab对单一扰动信号与混合扰动信号进行仿真验证,并与前人构造的形态非抽样小波进行对比分析。结果表明,所构造的形态非抽样小波具有很好的扰动信号特征描述能力及抗噪性能,即使在强噪声环境下,也能正确指示扰动起止时刻及突变极性,在电能质量扰动信号的检测定位上具有较好的适应性与可行性。Due mainly to the characteristics of scrambling and changeability of power quality disturbances, there is lack of mature methods for detection and location of PQ disturbances. Based on that, this paper constructed a new morphological undecimated wavelet （MUDW） and applied it to power quality disturbances location. The proposed MUDW composed of open-close and close-open morphology filter, and morphology gradient which can detect the verges of signals, the new MUDW satisfied signal reconstruction condition. Simulations of single disturbance and mixed disturbances are done utilizing Matlab and a comparison with other MUDW is analyzed, the results shows that the proposed MUDW has good ability of depicting-characteristics and anti-noise performance, even in the strong noise environment, it can indicate the instants of start and halt and disturbances polarity correctly. Consequently, the proposed MUDW is well adaptability and feasibility on detection and location of power quality disturbances.

关 键 词：电能质量 定位 形态非抽样小波 形态梯度 

分 类 号：TM761[电气工程—电力系统及自动化]