| 基于小波和进化网络的电能质量动态扰动自动识别 |
| |
| 引用本文： | 张智远,李庚银,冯任卿.基于小波和进化网络的电能质量动态扰动自动识别[J].华北电力大学学报,2002,29(3):1-4. |
| |
| 作者姓名： | 张智远 李庚银 冯任卿 |
| |
| 作者单位： | 华北电力大学电力工程系,河北,保定,071003 |
| |
| 基金项目： | 高等学校骨干教师资助计划资助(GG－470－10079－1001)． |
| |
| 摘 要： | 提出了一种基于小波和进化网络的电能质量动态扰动自动识别方法。首先应用Ｄａｕｂｅｃｈｉｅｓ ４小波对扰动波形进行分解,得到各个尺度上的小波系数,然后进行特征提取:采用遗传算法设计的模式特征分类器对扰动进行分类。实验表明该方法具有分类准确、网络学习速度快及收敛效果好等显著特点。
|
| 关 键 词： | 电能质量 扰动识别 小波变换 人工神经网络 遗传算法 |
| 文章编号： | 1007-2691(2002)03-0001-04 |
| 修稿时间： | 2002年1月1日 |
Auto recognition of power quality disturbance based on wavelet and genetic net |
| |
| ZHANG Zhi-yuan,LI Geng-yin,FENG Ren-qing.Auto recognition of power quality disturbance based on wavelet and genetic net[J].Journal of North China Electric Power University,2002,29(3):1-4. |
| |
| Authors: | ZHANG Zhi-yuan LI Geng-yin FENG Ren-qing |
| |
| Abstract: | A novel approach to detect and classify various types of power quality disturbances is presented in this paper. The wavelet Daubechies 4 is used to decompose the signals containing disturbances. The character vectors are extracted through the wavelet coefficients in five scales. Using the Genetic Algorithm (GA) based on the neural network the pattern characters can be classified by the mode classifier. Computation results show that the proposed method has good performance both in speed and in accuracy. |
| |
| Keywords: | power quality disturbance recognition wavelet neural network genetic algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
