引用本文: | 齐郑,李志,张首魁,等.基于复合结构元素的新型自适应形态滤波器设计[J].电力系统保护与控制,2017,45(14):121-127.[点击复制] |
QI Zheng,LI Zhi,ZHANG Shoukui,et al.Design of a new adaptive morphological filter based on composite structure elements[J].Power System Protection and Control,2017,45(14):121-127[点击复制] |
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摘要: |
针对电力系统信号采集中常见的噪声干扰问题,提出一种使用复合结构元素的自适应形态学滤波器。这种滤波器融合两种及以上结构元素作为复合结构元素,统计分析输入信号与拟输出滤波信号之间的滤波误差,寻找复合结构元素的整体最优尺度,从而优化滤波效果。根据滤波误差极大值原理,调整组成复合结构元素的两种元素的参数占比,进一步优化,可得最优滤波使用的复合结构元素。仿真实验对包含随机白噪声的电力信号进行自适应滤波,结果表明,在面向随机噪声时,所提出的自适应滤波器能够准确寻求到最优结构元素,滤波性能优于使用单一结构元素的传统形态滤波器,具有良好的应用前景。 |
关键词: 电力信号消噪 数学形态学 自适应滤波 复合结构元素 随机噪声 |
DOI:10.7667/PSPC161028 |
投稿时间:2016-07-07修订日期:2016-09-30 |
基金项目:国家自然科学基金(51277066) |
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Design of a new adaptive morphological filter based on composite structure elements |
QI Zheng,LI Zhi,ZHANG Shoukui,ZHANG Hongying |
(School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China) |
Abstract: |
In view of the common noise interference in the signal acquisition of power system, an adaptive morphological filter using composite structure elements is proposed. The adaptive filter combines two or more structure elements as the composite structure element. The filtering error between the input and output signals is analyzed to determine the integral size of the composite structure element that can make the filtering effect reach the optimum. Then the parameters of the two elements of composite structure elements are adjusted according to the filtering error maximum principle for further optimization. Finally the optimal composite structure element is obtained. Simulation experiment is carried out on the adaptive filtering of the power signal containing random white noise. The results show that the proposed adaptive filter can accurately find the optimal structure element in the face of random noise. Compared with the traditional morphological filter using a single structure element, it has better filtering performance and also has a good application prospects. This work is supported by National Natural Science Foundation of China (No. 51277066). |
Key words: power signal de-noising mathematical morphology adaptive filtering composite structure element random noise |