摘要
为消除基于互补集合经验模态分解(CEEMD)的谐波检测法易受到迭代次数与辅助白噪声的干扰而产生虚假分量与模态混叠等问题,以及CEEMD方法在检测噪声背景下的谐波信号精度不高的缺陷,提出一种基于排列熵(PE)算法与CEEMD相结合的PE-CEEMD谐波检测方法。首先对谐波信号进行互补集合经验模态分解,得到若干频率由高到低排列的固有模态函数(IMF),利用排列熵算法快速选定随机性较大的噪声分量进行剔除,对剩余信号再进行CEEMD分解。仿真实验数据表明,相较于CEEMD方法,PE-CEEMD方法能够较好地克服模态混叠与虚假分量等问题,并且针对复杂谐波信号的各次谐波频率成分与幅值的检测精度分别提高了4.424%与9.3%。
The harmonic detection method based on complementary ensemble empirical mode decomposition(CEEMD) is susceptible to the interference of iterations and auxiliary white noise, resulting in the defects of false component and mode mixing. And CEEMD method has the defect of low precision in detecting harmonic signal under noise background. To solve the above problems, a new PE-CEEMD harmonic detection method was proposed based on the combination of permutation entropy(PE) algorithm and CEEMD. Firstly, the harmonic signal is decomposed by CEEMD to obtain a series of intrinsic mode-functions(IMF) with frequency from high to low. The PE algorithm was used to quickly select and eliminate the noise components with large randomness, and then CEEMD decomposition was performed for the remaining signals. Simulation results show that PE-CEEMD method can overcome the problems of modal aliasing and false components better than CEEMD method, and the detection accuracy of frequency components and amplitude of complex harmonic signals is improved by 4.424% and 9.3%, respectively.
作者
张展
刘亚晨
杜诗扬
杨晋
Zhang Zhan;Liu Yachen;Du Shiyang;Yang Jin(School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454000,China)
出处
《电子测量技术》
北大核心
2022年第9期92-98,共7页
Electronic Measurement Technology
基金
矿山电力电子装置与控制科研团队基金(CXTD2017085)项目资助。
关键词
CEEMD
排列熵
模态混叠
虚假分量
谐波检测
complementary ensemble empirical mode decomposition
permutation entropy
mode mixing
false component
harmonic detection
