孔垂锐,陈凤仙,杨灵睿,车玉奎,杨海贤,夏巍,郭成
KONG Chuirui,CHEN Fengxian,YANG Lingrui,CHE Yukui,YANG Haixian,XIA Wei,GUO Cheng

• 1:云南电网有限责任公司曲靖马龙供电局
• 2:昆明理工大学电力工程学院

摘要(Abstract)：

针对EWT（经验小波变换）分解谐波信号时存在的对噪声敏感和过分解问题，提出了一种基于自适应小波和改进EWT的谐波与间谐波检测方法。首先，为了改善传统小波阈值函数效果，提出了一种自适应无参阈值函数；然后，通过EWT分析信号的频谱，得到一系列滤波组对信号进行分量分解；最后，引入DTW（动态时间规整）对过分解信号进行重构，得到最终的分量并辨识其频率和幅值。仿真结果表明，所提算法有效抑制了谐波中存在的噪声，并改善了EWT的过分解问题。通过与EMD（经验模态分解）和PSO-VMD（基于粒子群优化的变分模态分解）进行对比，验证了所提方法在分离谐波和间谐波检测方面的优越性。
To address the issues of noise sensitivity and over-decomposition when decomposing harmonic signals using empirical wavelet transform(EWT), a method based on adaptive wavelet denoising and improved EWT is proposed for detecting harmonics and interharmonics. Firstly, to enhance the effectiveness of traditional wavelet threshold functions, an adaptive parameterless threshold function is introduced. Then, by analyzing the signal spectrum using EWT, a series of filter banks is obtained to decompose the signal components. Finally, dynamic time warping(DTW) is employed to reconstruct the over-decomposed signals, resulting in the final components and identifying their frequencies and amplitudes. Simulation results demonstrate that the proposed method effectively suppresses noise in the harmonics and improves the over-decomposition of EWT. Comparison with empirical mode decomposition(EMD) and particle swarm optimization based variational mode decomposition(PSO-VMD) verifies the superiority of the proposed method in separating harmonics and detecting interharmonics.

关键词(KeyWords)： 谐波;间谐波;EWT;小波阈值函数;DTW
harmonic;interharmonic;EWT;wavelet threshold function;DTW

Abstract:

Keywords:

基金项目(Foundation): 云南省联合基金重点项目（202201BE070001-15）;; 云南电网公司科技项目（YNKJXM20220053）

作者(Author): 孔垂锐,陈凤仙,杨灵睿,车玉奎,杨海贤,夏巍,郭成
KONG Chuirui,CHEN Fengxian,YANG Lingrui,CHE Yukui,YANG Haixian,XIA Wei,GUO Cheng

DOI: 10.19585/j.zjdl.202411011

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