摘要
针对经验模态分解(EMD)在谐波检测应用中产生模态混叠的问题,结合EMD分解的局限性和谐波检测实际情况进行分析。首先用集合经验模态分解(EEMD)消除EMD遇到间歇信号干扰出现的模态混叠问题,然后根据谐波信号间的密频问题,提出了基于Hilbert频移的EEMD谐波检测方法。该方法先对谐波信号进行EEMD分解,通过相关度判断相近信号是否发生混叠,若发生混叠,利用Hilbert频移方法使信号满足EEMD分解条件,从而将其分解为单频率分量信号。经仿真验证,该方法能够很好地克服谐波检测中的间歇信号干扰和信号间密频问题,保证了谐波信号有效分解和实用性。通过对实际整流信号的分析证明该方法具有很好的检测效果。
To solve the modal mixing problem of EMD in the applications of harmonic detection, this paper analyzes the problem combined with the boundedness of EMD in' the decomposition process and the practical situation of harmonic detection. Firstly, this paper uses the EEMD method to eliminate the modal mixing problem caused by the interference of intermittent signal. Secondly, aiming at the mixing problem of dense frequency signal, it proposes the EEMD harmonic detection method based on the frequency shift of Hilbert. This method decomposes harmonic signal in EEMD, and then uses the correlation to judge whether it is mixed with close signals. If there is the modal mixing problem, it will use the frequency shift of Hilbert to make the signal satisfy the decomposition condition of EEMD, thus decompose the complex signal into many single signals. The simulation verifies that the method can effectively overcome the problems caused by the interference of intermittent signal and dense frequency signal in the harmonic detection and meanwhile insure the effective decomposition and the practicabilityl The analysis of the actual rectified signal proves that the method has a good detection result.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2017年第15期85-91,共7页
Power System Protection and Control
基金
天津市科技支撑重点项目(12ZCZDGX01400)
河北省教育厅资助科研项目(ZD2016108)
河北工业大学博士科研启动费资助项目