基于经验模态分解的纸机横向定量测量数据去噪  

Noise Removal of Cross-directional Basis Weight Measured Data on Paper Machines Based on EMD

作　　者：汤伟[1] 连钰洋 胡连华 刘文波[1] 王孟效 

机构地区：[1]陕西科技大学电气与信息工程学院,陕西西安710021 [2]陕西西微测控技术有限公司,陕西咸阳712000

出　　处：《中国造纸》2015年第3期44-48,共5页China Pulp & Paper

基　　金：陕西省科技统筹项目(2014KCT-15);陕西省教育厅科研计划项目(2013JK1063);陕西省教育厅自然科学研究项目(2013JK1062);陕西省科技计划经费资助项目(2014K05-03)

摘　　要：针对传统去噪算法不能满足更高质量横向定量控制要求,提出一种基于经验模态分解(Empirical Mode Decomposition,EMD)的去噪方法。该方法利用EMD分解时间尺度的特性和自适应性,通过去除高频分量并进行滑动平均滤波达到去噪效果。仿真结果表明,这种算法能有效地滤除噪声,同时又保留定量主要细节,有利于进行后续控制。As conventional noise removal methods were not able to meet the requirement of higher performance cross-directional basis weight control,a new method based on EMD was proposed. The method achieved noise removal by removing the high-frequency component and moving average filter based on time scale features and adaptability of EMD. The simulation results showed that the method had good noise removal effect. The gained data retained the main details of basis weight,which was conducive to subsequent control.

关 键 词：横向定量 去噪 经验模态分解 

分 类 号：TN911.4[电子电信—通信与信息系统]