Gram多项式拟合在纸机横向定量测量数据去噪中的应用

Application of Gram Polynomials Fitting Technique in Noise Removal of Cross-directional Basis Weight Measurement Data of Paper Machines

中文关键词:  横向定量  去噪  Gram多项式  最小二乘估计

Key Words:cross-directional basis weight  noise removal processing  Gram polynomials

中文摘要:

      针对传统去噪算法不能满足更高品质的横向定量控制要求的问题，提出了一种Gram多项式拟合的去噪方法。仿真结果显示该方法对于高斯噪声和均匀分布噪声都具有良好的去噪效果。对于纸机横向定量测量数据，该方法去噪效果光滑性好，测量数据更接近纸张定量真实值。

Abstract:

      As conventional noise removal methods can not meet the requirement of higher performance cross-directional basis weight control, a new method using Gram polynomials fitting technique was proposed. The simulation results showed that the method had good noise removal effect for Gaussian noise and uniform noise. After the cross-directional basis weight measurement data was processed, the gained data was smooth and it was closer to the true basis weight of the paper．