Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network

Yaoguang Hu; Xi Cheng; Xiangmin Cui; Ruijun Zhang; Yan Yan

doi:10.1109/IEEM.2010.5674326

Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network

Yaoguang Hu^*, Xi Cheng, Xiangmin Cui, Ruijun Zhang, Yan Yan

^*Corresponding author for this work

School of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

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.

Original language	English
Title of host publication	IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management
Pages	1438-1442
Number of pages	5
DOIs	https://doi.org/10.1109/IEEM.2010.5674326
Publication status	Published - 2010
Event	IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010 - Macao, China Duration: 7 Dec 2010 → 10 Dec 2010

Publication series

Name	IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management

Conference

Conference	IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010
Country/Territory	China
City	Macao
Period	7/12/10 → 10/12/10

Keywords

BP neural network
Data-driven soft sensor
Inverse model
MIMO
Quality control

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10.1109/IEEM.2010.5674326

Cite this

Hu, Y., Cheng, X., Cui, X., Zhang, R., & Yan, Y. (2010). Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network. In IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1438-1442). Article 5674326 (IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management). https://doi.org/10.1109/IEEM.2010.5674326

@inproceedings{2d9c79b88a014faebf280378d0286c52,

title = "Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network",

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 = "BP neural network, Data-driven soft sensor, Inverse model, MIMO, Quality control",

author = "Yaoguang Hu and Xi Cheng and Xiangmin Cui and Ruijun Zhang and Yan Yan",

year = "2010",

doi = "10.1109/IEEM.2010.5674326",

language = "English",

isbn = "9781424485031",

series = "IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management",

pages = "1438--1442",

booktitle = "IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management",

note = "IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010 ; Conference date: 07-12-2010 Through 10-12-2010",

}

Hu, Y, Cheng, X, Cui, X, Zhang, R & Yan, Y 2010, Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network. in IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management., 5674326, IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1438-1442, IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010, Macao, China, 7/12/10. https://doi.org/10.1109/IEEM.2010.5674326

Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network. / Hu, Yaoguang; Cheng, Xi; Cui, Xiangmin et al.
IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management. 2010. p. 1438-1442 5674326 (IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network

AU - Hu, Yaoguang

AU - Cheng, Xi

AU - Cui, Xiangmin

AU - Zhang, Ruijun

AU - Yan, Yan

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - BP neural network

KW - Data-driven soft sensor

KW - Inverse model

KW - MIMO

KW - Quality control

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U2 - 10.1109/IEEM.2010.5674326

DO - 10.1109/IEEM.2010.5674326

M3 - Conference contribution

AN - SCOPUS:78751697493

SN - 9781424485031

T3 - IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management

SP - 1438

EP - 1442

BT - IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management

T2 - IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010

Y2 - 7 December 2010 through 10 December 2010

ER -

Hu Y, Cheng X, Cui X, Zhang R, Yan Y. Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network. In IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management. 2010. p. 1438-1442. 5674326. (IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management). doi: 10.1109/IEEM.2010.5674326

Soft sensor modeling of feed liquid viscosity control for PVC gloves based on BP neural network

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