摘要
光栅莫尔条纹的信号质量直接决定其测量精度,将基于变分模态分解(VMD)的方法用于对光栅莫尔条纹信号的去噪处理。首先对莫尔条纹仿真信号进行VMD分解成若干个不同频率段的本征模态函数(IMF);然后利用希尔伯特变换对IMF分量时频特性进行分析,滤除高频噪声信号。结果表明:与经验模态分解(EMD)算法的分解结果相比,VMD算法能够很好地抑制模态混叠现象,准确地将不同频率段的信号分解出来,而且提高了去噪之后信号的信噪比,去噪效果好。
The signal quality of grating Moire fringe directly determines its measurement accuracy. The method based on variational mode decomposition (VMD) is used to denoise the grating Moire fringe signal. The simulation signal of Moire fringe is decomposed into several intrinsic mode functions (IMF) in different frequency bands by VMD, and then the time-frequency characteristics of IMF components are analyzed by Hilbert transform to filter out high-frequency noise signals. The results show that compared with empirical mode decomposition(EMD) decomposition results, VMD algorithm can effectively suppress the mode aliasing phenomenon, accurately decompose the signals of different frequency bands, and improve the signal-to-noise ratio of the signal after denoising, the denoising effect is well.
作者
鲍克勤
卢丹
吴文峰
陈丹
BAO Keqin;LU Dan;WU Wenfeng;CHEN Dan(Shanghai University of Electric Power, Shanghai 200090, China;State Grid Bengbu power supply company, Bengbu Anhui 233000, China)
出处
《光通信技术》
北大核心
2019年第1期28-31,共4页
Optical Communication Technology
基金
国家自然科学基金(61573239)资助
关键词
光栅莫尔条纹
变分模态分解
去噪
本征模态函数
希尔伯特变换
经验模态分解
grating Moire fringe
variational mode decomposition
denoising
intrinsic mode function
Hilbert transform
empirical mode decomposition
