| .基于改进PSO-WNN的电能质量扰动分类研究[J].电气自动化,2011,(5): |
| 基于改进PSO-WNN的电能质量扰动分类研究 |
| Power Quality Disturbances Classification Based on Improved PSO-WNN |
| |
| DOI： |
| 中文关键词: 电能质量扰动 改进粒子群算法 小波神经网络 分类识别 |
| 英文关键词:power quality disturbances particle swarm optimization wavelet neural network classification |
| 基金项目: |
|
|
| 摘要点击次数: 2558 |
| 全文下载次数: 26 |
| 中文摘要: |
| 提出一种基于改进粒子群算法和小波神经网络相结合的电能质量扰动分类方法。首先利用小波多分辨技术检测电能质量扰动信号,然后提取各类扰动能量特征向量,将此特征向量输入到优化后的小波神经网络进行识别,最后经改进粒子群小波神经网络得到电能质量扰动分类结果。实例仿真计算结果表明,方法可大大提高电能质量扰动分类识别能力。 |
| 英文摘要: |
| This paper introduces a method for classifying duration power quality disturbances(DPQDs) ,which is based on particle swarm optimization and wavelet neural network.first,power quality disturbance signals are detected with Wavelet multiresolution analysis technique;then,all kinds of disturbance energy feature vector are input into the p optimized wavelet neural network to identify power quality disturbance types;finally,the classify records of power quality disturbance was achieved.Numerical simulation resul... |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |
|
|
|
