基于CEEMD-WPT和Prony算法的谐波间谐波参数辨识  

Parameter identification of harmonics and inter-harmonics based on CEEMD-WPT and Prony algorithm

作　　者：张煜林 陈红卫[1] ZHANG Yulin;CHEN Hongwei(School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China)

机构地区：[1]江苏科技大学电子信息学院,江苏镇江212003

出　　处：《电力系统保护与控制》2018年第12期115-121,共7页Power System Protection and Control

基　　金：江苏省支撑计划基金项目资助(BE2013011-3)~~

摘　　要：由于传统Prony算法对噪声极为敏感,因此采用互补集合经验模态分解(CEEMD)和小波包变换(WPT)相结合的去噪方法改善信号,提高Prony参数辨识的精度。首先对信号进行CEEMD分解得到固有模态函数(IMF),并对得到的IMF分量计算其排列熵(PE)值,根据排列熵值提取出含噪声较大的分量进行小波包去噪。然后将去噪重构后的IMF分量与剩余IMF分量重构信号。最后用Prony算法辨识重构后信号的参数。对所提算法进行仿真,并与已发表文献中的结果进行比较。仿真与比较结果表明,该算法是有效的,而且具有较好的辨识结果。Since traditional Prony algorithm is extremely sensitive to noise, the Complementary Ensemble Empirical Mode Decomposition（CEEMD） and wavelet packet transform combined denoising method is used to improve the signal and enhance the Prony parameter identification accuracy. Firstly, the Intrinsic Mode Functions（IMF） are obtained through decomposing the signal with CEEMD method and their Permutation Entropy（PE） is calculated. Secondly, the high noise level IMFs which are extracted according to the values of the PE are processed with wavelet packet denoising. Thirdly, original signal is reconstructed by the IMFs which are processed and the rest IMFs. Finally, the parameters of reconstructed signal are identified with Prony algorithm. The algorithm proposed is simulated and compared with the literature results, the simulation and comparison results show that the algorithm is effective and has better identification results.

关 键 词：PRONY算法 CEEMD 小波包变换 排列熵 参数辨识 

分 类 号：TM761[电气工程—电力系统及自动化]