摘要
为抑制经验模态分解(empirical mode decomposition,EMD)处理过程中的端点效应,在整理和研究现有方法的基础上,提出一种镜像延拓和极值平移相结合的端点处理方法,在最大程度地融合两种传统方法优点的同时尽可能地还原信号边界特征。该方法通过构造特征平行四边形使延拓极值处于理想区域,从而避免三次样条差值过程中包络线与信号交叉的产生,并引入Blackman窗函数对延拓信号进行边界处理,进而有效地控制延拓误差影响。经过仿真信号验证与实测信号分析,对比镜像延拓、极值平移与加窗边界处理方法的端点抑制效果,证明该改进方法能有效地抑制分解过程中出现的端点效应,并能在高频噪声干扰下较完整地提取低频信息,为燃气轮机工频特征的获取提供可靠的保证。
In order to dispose the end effect during empirical mode decomposition （EMD）, there comes the improved EMD. The treatment of end effect decides the extraction of signal time- frequency characteristics. Based on the study of current approaches, an effective method has been proposed in combination with mirror extension and extreme point shifting. The new method comprises the merits of the two traditional approaches and serves as the maximum restoration of signal boundary characteristics. A characteristics parallelogram has been constructed to circumscribe the prolongation extremum within an ideal region, thus preventing the envelope curve from intersecting with the signal during the process of cubic spline interpolation. Blackman window function has been introduced to dispose the extended signal boundary so as to control the influence of prolongation errors. The simulation test and actual measurement show that the method can effectively restrain end diffusion and completely extract low frequency information under the interference of high-frequency noise, compared to mirror extension, extreme point shifting and windowing boundary treatment.
出处
《中国测试》
CAS
北大核心
2016年第1期107-113,共7页
China Measurement & Test
基金
军队通保科研基金(装通[2012]80号)
