Articles & Issues
- Language
- English
- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
-
Received January 29, 2020
Accepted March 22, 2020
-
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright © KIChE. All rights reserved.
All issues
Estimation of basis weight, ash content and moisture content in papermaking plants: A comparative study
Department of Chemical Engineering, Hanyang University, Seoul 04763, Korea
Korean Journal of Chemical Engineering, July 2020, 37(7), 1107-1115(9), 10.1007/s11814-020-0549-7
Download PDF
Abstract
The papermaking process is a typical nonlinear process with multiple input-output variables, so it is difficult to construct an accurate model for the process. Data-based modeling techniques may be used to establish a reliable paper plant model. In particular, the LSSVM (least-squares support vector machine) can be used to create a highperformance papermaking process model based on operation data. In this paper, we present a paper plant model that can predict three key output variables (basis weight, ash content, moisture content) with four input variables (stock flow, filler flow, speed, steam pressure) using LSSVM. The proposed LSSVM model is compared with other data-based models (the ANN (artificial neural network) model and the state-space model). The LSSVM model turned out to exhibit better estimation performance compared to others.
References
Norman B, The water and fiber flow system in the paper and board mill, EUCEPA, Paris (1990).
Mardon J, Jackson M, Serenius R, Appita J., 25, 45 (1971)
Fu Y, Dumont GA, Control Eng. Pract., 3(10), 1487 (1995)
Kuusisto R, Kosonen M, Shakespeare J, Huhtelin T, Pulp Pap. Can., 103(10), 28 (2002)
Kim DH, Yeo YK, Park SH, Gang H, J. of Korea Technical Association of the Pulp and Paper Industry, 35(4), 48 (2003).
Yeo YK, Yi SC, Ryu JY, Kang H, Korean J. Chem. Eng., 21(2), 358 (2004)
Yeo YK, Hwang KS, Yi SC, Kang H, Korean J. Chem. Eng., 21(4), 761 (2004)
Edwards PJ, Murray AF, Papadopoulos G, Wallace AR, Barnard J, Smith G, IEEE Trans. Neural Networks, 10(6), 1456 (1999)
Wang H, Oyebande B, IEEE Proceedings of International Conference on Control Applications, 657 (1995).
Khanduja R, Tewari PC, Chauhan RS, Kumar D, Jordan J. of Mechanical and Industrial Engineering, 4(4), 487 (2010).
Suykens JAK, Vandewalle J, Neural Process Letters, 9(3), 293 (1999)
Wang H, Wang AP, Duncan SR, Advanced process control in paper and board making, Pira International, UK (1997).
Hagan MT, Demuth HB, Beale MH, Neural network design, PWS Publishing company, Boston, MA (1996).
Tian YD, Zhu XJ, Cao GY, J. Univ. Sci. Technol. Beijing, 12, 72 (2005)
Suykens JAK, IEEE Instrumentation and Measurement Technology Conference, 287 (2001).
Pijush S, Scientific Research, 3, 431 (2011)
Haifeng W, Dejin H, IEEE 2005 International Conference on Neural Networks and Brain, 279 (2005).
Mardon J, Jackson M, Serenius R, Appita J., 25, 45 (1971)
Fu Y, Dumont GA, Control Eng. Pract., 3(10), 1487 (1995)
Kuusisto R, Kosonen M, Shakespeare J, Huhtelin T, Pulp Pap. Can., 103(10), 28 (2002)
Kim DH, Yeo YK, Park SH, Gang H, J. of Korea Technical Association of the Pulp and Paper Industry, 35(4), 48 (2003).
Yeo YK, Yi SC, Ryu JY, Kang H, Korean J. Chem. Eng., 21(2), 358 (2004)
Yeo YK, Hwang KS, Yi SC, Kang H, Korean J. Chem. Eng., 21(4), 761 (2004)
Edwards PJ, Murray AF, Papadopoulos G, Wallace AR, Barnard J, Smith G, IEEE Trans. Neural Networks, 10(6), 1456 (1999)
Wang H, Oyebande B, IEEE Proceedings of International Conference on Control Applications, 657 (1995).
Khanduja R, Tewari PC, Chauhan RS, Kumar D, Jordan J. of Mechanical and Industrial Engineering, 4(4), 487 (2010).
Suykens JAK, Vandewalle J, Neural Process Letters, 9(3), 293 (1999)
Wang H, Wang AP, Duncan SR, Advanced process control in paper and board making, Pira International, UK (1997).
Hagan MT, Demuth HB, Beale MH, Neural network design, PWS Publishing company, Boston, MA (1996).
Tian YD, Zhu XJ, Cao GY, J. Univ. Sci. Technol. Beijing, 12, 72 (2005)
Suykens JAK, IEEE Instrumentation and Measurement Technology Conference, 287 (2001).
Pijush S, Scientific Research, 3, 431 (2011)
Haifeng W, Dejin H, IEEE 2005 International Conference on Neural Networks and Brain, 279 (2005).
