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文章摘要
一种基于小波包变换的电力系统谐波检测方法
A harmonic detection method for power system based on wavelet packet transform
Received:January 22, 2017  Revised:January 22, 2017
DOI:
中文关键词: 小波包变换  希尔伯特变换  谐波  电能质量
英文关键词: wavelet packet transform  Hilbert transform  harmonics  power quality
基金项目:国家自然科学基金项目( 重点项目)(基于粒子滤波的统一电能质量分析理论研究,编号:51277080)
Author NameAffiliationE-mail
Xiao Xiaying State Key Laboratory of Advanced Electromagnetic Engineering and Technology,Huazhong University of Science and Technology 283051809@qq.com 
Li Kaicheng* State Key Laboratory of Advanced Electromagnetic Engineering and Technology,Huazhong University of Science and Technology likaicheng@mail.hust.edu.cn 
Wang lingyun State Key Laboratory of Advanced Electromagnetic Engineering and Technology,Huazhong University of Science and Technology 244149123@qq.com 
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中文摘要:
      非线性设备的大量使用和分布式电源的投入使得谐波污染愈加严重,本文提出了一种基于小波包变换的谐波检测方法,能对电能质量进行有效的分析。该方法在五层db40小波包变换的基础上,利用希尔伯特变换做移频运算,避免了中间频段小波混叠对检测精度造成的不利影响,并将各次谐波分量转移到精度较高的边频带进行小波包分解并重构信号,实现了各次谐波的高精度检测,同时通过Matlab工具对不同算法的仿真进行了比较和误差分析。仿真表明,相比于传统傅里叶变换,该算法具有高分辨率时频分析能力,能有效定位暂态干扰;与经典小波包变换相比,测量精度也有了较为明显的提高,实验结果一致显示了该算法的可行性和优越性。
英文摘要:
      As the widely use of the non-linear equipment and distribution generation, the harmonic pollution is becoming increasingly severe. Harmonic detection is a major topic in power quality (PQ) analysis. In this paper, an improved algorithm is proposed. This algorithm is based on the five-layer db40 wavelet packet transform (WPT). In order to reduce wavelet aliasing in the middle band, and the Hilbert transform (HT) is used for frequency shift so that the harmonic components are transferred to the marginal band with a better accuracy. Then the shifted signal is decomposed and reconstructed by the WPT for high-accuracy detection of the harmonics. Simulation of different algorithms and errorSanalysisSare also given in this paper. The results show that: this algorithm has a better ability of high-resolution time-frequency analysis and can detect the transientSdisturbance more effectively compared with the traditional Fourier transform, and more accurate than WPT.
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