Multi-rate principal component regression model forsoft sensor application in industrial processes  

作　　者：Le ZHOU Yaoxin WANG Zhiqiang GE 

机构地区：[1]State Key Laboratory of Industrial Control Technology,Zhejiang University,Hangzhou 310027,China [2]School of Automation and Electrical Engineering,Zhejiang University of Science and Technology,Hangzhou 310023,China [3]Hangzhou SIASUN Robot and Automation Co.,LTD.,Hangzhou 311225,China

出　　处：《Science China(Information Sciences)》2020年第4期226-228,共3页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China(Grant Nos.61603342);NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(Grant No.U1609214);China Postdoctoral Science Foundation(Grant No.2018M630674)。

摘　　要：Dear editor,For obtaining the accurate and timely information from the modern process industries,an increasing number of online hardware sensors are equipped for process monitoring and control,energy management and environmental protection purpose[1,2].However,some key variables of the process cannot be measured by these online sensors,which requires the off-line laboratory analysis.For solving these problems,an inferential model called soft sensor is usually utilized[3].

关 键 词：HARDWARE EDITOR equipped 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]