天津工业大学学报2017，Vol.36Issue(2)：54-58,5.DOI:10.3969/j.issn.1671-024x.2017.02.010
基于动态数据的上浆率在线增量软测量
Incremental online soft sensor for sizing percentage based on dynamic data
摘要
Abstract
Aiming at the dynamic data come from sizing process, a new incremental online algorithm was proposed to estab-lish soft sensor model for the prediction of sizing percentage. In order to improve the efficiency of algorithm , in-cremental learning method was introduced to reduce the redundant. The improved mountain method was used to determine the center point of data, and with the help of adaptive radius, the noisy data had been deleted. Final-ly, the soft sensor method was chosen to build the model. The experimental data came from the real sizing pro-cess, the simulation result demonstrated that the soft sensor model based on incremental online algorithm has the best accuracy and anti-noisy performance. The minimum of RMSE is 0.2633 and the minimum of MAE is 0.6331. At the same time, it is suitable for the online update of a variety of intelligent algorithms.关键词
上浆率/动态数据/增量学习/软测量/山峰算法/在线检测Key words
sizing percentage/dynamic data/incremental learning/soft sensor/mountain method/online detection分类
轻工纺织引用本文复制引用
田慧欣,彭晓..基于动态数据的上浆率在线增量软测量[J].天津工业大学学报,2017,36(2):54-58,5.基金项目
国家自然科学基金资助项目(61403277) （61403277）
