|
| 摘要: |
| 电能质量扰动的分类分为信号特征提取和分类器2个阶段,采用S变换和支持向量机构造电能质量复合扰动的分类识别方案.利用S变换进行扰动信号特征提取,构造支持向量机静态分类树,再通过基于Mercer核的聚类方法对静态分类树进行动态扩展,形成动态分类树,实现对复合扰动的识别.给出了电能质量复合扰动分类算法的4个步骤:构建静态分类树;用基于Mercer核的聚类方法进行聚类分析;构建动态分类树;对新发现的扰动确定其具体类型,并给其命名.算例表明该方法不仅可以有效分类识别电压突降、电压突升、电压中断、暂态振荡、电压尖峰、电压缺口和谐波等7种电能质量扰动,还可以识别由其组合而成的电能质量复合扰动. |
| 关键词: 电能质量 复合扰动 S变换 支持向量机 分类 特征提取 |
| DOI： |
| 分类号:TM933.4 |
| 基金项目: |
|
| Classification of power quality complex disturbances |
|
ZHAN Yong1 2 CHENG Haozhong2
|
| Abstract: |
| The classification of power quality disturbances has two sequential stages:signal feature extraction and classifier design. An approach based on SVM(Support Vector Machines) and S-transform to detect and classify power quality complex disturbances is presented. The features of disturbances are extracted by S-transform to construct the static SVM classification tree,which is then dynamically expanded based on Mercer Kernel clustering algorithm to classify power quality complex disturbances. Four steps of pow... |
| Key words: power quality complex disturbance S-transform support vector machines classification feature extraction |
