摘要
Aimed at the problem of the end effect when using empirical mode decomposition(EMD),a method for constraining the end effect of EMD is proposed based on sequential similarity detection and adaptive filter.The method divides the signal into many wavelets,and it changes the initial wavelet length to select the best initial wavelet that has the minimum error and maximum number of matching seed wavelets,and the wavelet slopes are used for pre-matching and secondary matching to speed up the matching speed.Then,folded self-adaptive threshold is used to select multiple seed wavelets,and finally the end waveform is predicted and expanded according to the adaptive filter method.The proposed method is used to analyze the non-stationary nonlinear simulation signal and experimental signal,and it is compared with the mirror extension and RBF extension methods.The orthogonality index and similarity index of the EMD results of the extended signal after the proposed method are better than those of the other methods.The results show that the proposed method can better constrain the end effect,and has certain validity,accuracy and stability in solving the end effect problem.
针对经验模态分解时存在的端点效应问题,提出了一种基于序贯相似度检测和自适应滤波的方法来抑制EMD的端点效应.该方法将信号分成多个子波,通过改变初始子波的长度来选择误差最小、匹配种子子波个数最大的最佳初始子波,并利用子波斜率进行预匹配和二次匹配,以提高匹配速度.然后利用对折方式自适应调整阈值选择多个种子小波,最后根据自适应滤波方法对端点波形进行预测和扩展.利用该方法对非平稳非线性仿真信号和实验信号进行了分析,并与镜像拓延法和RBF拓延法进行了比较,该方法拓延后信号的EMD结果正交指数和相似指数优于其他方法.结果表明,该方法能较好地抑制端点效应,对解决端点效应问题具有一定的有效性、准确性和稳定性.
基金
The National Natural Science Foundation of China(No.51675100).
