DocumentCode :
1824207
Title :
Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network
Author :
Yaoguang, Hu ; Xi Cheng ; Xiangmin, Cui ; Ruijun, Zhang ; Yan, Yan
Author_Institution :
Sch. of Mech. Eng., Beijing Inst. of Technol., Beijing, China
fYear :
2010
fDate :
7-10 Dec. 2010
Firstpage :
1438
Lastpage :
1442
Abstract :
In the plastics Industry, feed liquid viscosity is always a vital input factor to the quality of final products, but difficult to realize real time measurement. Thus, in this paper, a data-driven soft sensor was developed to help control the viscosities of feed liquid in the production of PVC gloves which contribute a lot to the final quality and rating of gloves on the basis of literature review and study. BP neural network was selected to build the MIMO control model after discussing the methods in data pre-processing. The result shows that the inverse quality model has good performance in deciding the input values of feed liquid viscosity.
Keywords :
MIMO systems; backpropagation; neurocontrollers; plastics industry; process control; quality control; viscosity; BP neural network; MIMO control; PVC gloves; data-driven soft sensor; feed liquid viscosity control; plastics industry; soft sensor modeling; Artificial neural networks; Biological system modeling; Data models; Feeds; Production; Transducers; Viscosity; BP neural network; MIMO; Quality control; data-driven soft sensor; inverse model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference on
Conference_Location :
Macao
ISSN :
2157-3611
Print_ISBN :
978-1-4244-8501-7
Electronic_ISBN :
2157-3611
Type :
conf
DOI :
10.1109/IEEM.2010.5674326
Filename :
5674326
Link To Document :
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