Ink feed control in a web-fed offset printing press

被引:7
作者
Englund, Cristofer [1 ]
Verikas, Antanas [1 ,2 ]
机构
[1] Halmstad Univ, Intelligent Syst Lab, S-30118 Halmstad, Sweden
[2] Kaunas Univ Technol, Dept Appl Elect, LT-51368 Kaunas, Lithuania
关键词
Ink feed control; Colour printing; Multiple models; Integrating controller; Neural networks;
D O I
10.1007/s00170-007-1273-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Automatic and robust ink feed control in a web-fed offset printing press is the objective of this work. To achieve this goal an integrating controller and a multiple neural models-based controller are combined. The neural networks-based printing process models are built and updated automatically without any interaction from the user. The multiple models-based controller is superior to the integrating controller as the process is running in the training region of the models. However, the multiple models-based controller may run into generalisation problems if the process starts operating in a new part of the input space. Such situations are automatically detected and the integrating controller temporary takes over the process control. The developed control configuration has successfully been used to automatically control the ink feed in the web-fed offset printing press according to the target amount of ink. Use of the developed tools led to higher print quality and lower ink and paper waste.
引用
收藏
页码:919 / 930
页数:12
相关论文
共 15 条
[1]   The development of a connectionist expert system for compensation of color deviation in offset lithographic printing [J].
Almutawa, S ;
Moon, YB .
ARTIFICIAL INTELLIGENCE IN ENGINEERING, 1999, 13 (04) :427-434
[2]  
BRALASUBRAMANIA.R, 1999, J ELECTRON IMAGING, V8, P156
[3]   Machine vision in conjunction with a knowledge-based system for semi-automatic control of a gravure printing process [J].
Brown, N ;
Jackson, MR ;
Parkin, RM ;
Bamforth, PE .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2004, 218 (I7) :583-593
[4]  
CHEN L, 2001, P AM CONTR C IEEE CH, V6, P4199
[5]   A SOM-based data mining strategy for adaptive modelling of an offset lithographic printing process [J].
Englund, C. ;
Verikas, A. .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2007, 20 (03) :391-400
[6]  
Englund C, 2005, LECT NOTES COMPUT SC, V3496, P461
[7]  
ENGLUND C, 2006, COMP IND ENG UNPUB
[8]   A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems [J].
Herzallah, R ;
Lowe, D .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2004, 17 (02) :145-158
[9]   Model-based halftoning of color images [J].
Pappas, TN .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1997, 6 (07) :1014-1024
[10]  
POPE B, 2000, TAGA 2000 P, P417