| 摘要: |
| 提出了一种基于聚类经验模态分解（EEMD）的希尔伯特-黄变换（HHT）电能质量扰动检测新方法。首先采用EEMD对电能质量扰动信号进行分解，获得固有模态函数后，再进行HHT，可以定量、准确地刻画相应时刻的瞬时特征量。该方法可以确定非平稳的电能质量扰动信号的时间、频率和幅值等信息。仿真试验结果表明，该方法可以有效克服经验模态分解方法存在的模态混叠和过零失效问题，同时也适用于混合电能质量扰动的检测。 |
| 关键词: 电能质量 希尔伯特-黄变换 模态混叠 聚类经验模态分解 扰动检测 白噪声 应用 |
| DOI： |
| 分类号: |
| 基金项目:教育部新世纪优秀人才支持计划项目（NECT080825）；霍英东教育基金会高等院校青年教师基金资助项目（101060） |
|
| Application of EEMD in power quality disturbance detection |
|
ZHANG Yang1, LIU Zhigang2
|
|
1.School of Electrical Engineering，Southwest Jiaotong University，Chengdu 610031，China;2.School of Electrical Engineering，Southwest Jiaotong University，Chengdu 610032，China
|
| Abstract: |
| Detection of power quality disturbance based on EEMD（Ensemble Empirical Mode Decomposition） and HHT（Hilbert-Huang Transform） is introduced. Power quality disturbance signal is decomposed into IMF （Intrinsic Mode Function） based on EEMD and the instantaneous attribute of corresponding time is then detected accurately and quantitatively by HHT，including time，amplitude and frequency. Simulative results show that it effectively avoids the mode mixing and zero-crossing failure caused by EMD（Empirical Mode Decomposition），suitable for the detection of multiple power quality disturbances as well. |
| Key words: power quality Hilbert-Huang transform mode mixing EEMD disturbance detection white noise applications |
