Abstract
This paper is concerned with a multi–resolution tool for screening paper formation variations in various frequency regions on production line. A paper web is illuminated by two red diode lasers and the reflected light recorded as two time series of high resolution measurements constitute the input signal to the papermaking process monitoring system. The time series are divided into blocks and each block is analyzed separately. The task is treated as kernel based novelty detection applied to a multi–resolution time series representation obtained from the band-pass filtering of the Fourier power spectrum of the series. The frequency content of each frequency region is characterized by a feature vector, which is transformed using the canonical correlation analysis and then categorized into the inlier or outlier class by the novelty detector. The ratio of outlying data points, significantly exceeding the predetermined value, indicates abnormalities in the paper formation. The tools developed are used for online paper formation monitoring in a paper mill.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Kaestner, A., Nilsson, C.M.: Estimating the relative shrinkage profile of newsprint. Optical Engineering 42(5), 1467–1475 (2003)
Verikas, A., Malmqvist, K., Bergman, L., Engstrand, P.: Colour speck counter for assessing the dirt level in secondary fibre pulps. Journal of Pulp and Paper Science 29(7), 220–224 (2003)
Bacauskiene, M., Verikas, A.: The evidence theory based post-processing of colour images. Informatica 15(3), 315–328 (2004)
Norman, B., Wahren, D.: The measurement of mass distribution in paper sheet using a beta radiographic method. Svensk Papperstidning 77(11), 397–406 (1974)
Trepanier, R.J., Jordan, B.D., Nguyen, N.G.: Specific perimeter: a statistic for assessing formation and print quality by image analysis. TAPPI Journal 81, 191–196 (1998)
Bouydain, M., Colom, J.F., Navarro, R., Pladellorens, J.: Determination of paper formation by Fourier analysis of light transmission images. Appita Journal 54(2), 103–105 (2001)
Turtinen, M., Pietikainen, M., Silven, O., Maenpaa, T., Niskanen, M.: Paper characterisation by texture using visualisation-based training. International Journal of Advanced Manufacturing Technology 22(11-12), 890–898 (2003)
Keller, D.S., Lewalle, J., Luner, P.: Wavelet Analysis of Simulated Paper Formation. Paperi ja Puu 81(7), 499–505 (1999)
Nesic, Z., Davies, M., Dumont, G.: Paper Machine Data Analysis and Compression using Wavelets. Tappi Journal 80(10), 191–204 (1997)
Timberlake, A., Strom, E.: Do You Know What Causes the Variability in the Paper You Produce? In: 2004 Paper Summit, Spring Technical & International Environmental Conference, TAPPI Proceedings (2004)
Shawe-Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis. Cambridge University Press, Cambridge (2004)
Ejnarsson, M., Nilsson, C.M., Verikas, A.: A kernel based multi-resolution time series analysis for screening deficiencies in paper production. In: Wang, J., Yi, Z., Zurada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol. 3973, pp. 1111–1116. Springer, Heidelberg (2006)
Kuss, M., Graepel, T.: The geometry of kernel canonical correlation analysis. Technical Report 108, Max Planck Institute for Biological Cybernetics (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Ejnarsson, M., Nilsson, C.M., Verikas, A. (2007). Screening Paper Formation Variations on Production Line. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_51
Download citation
DOI: https://doi.org/10.1007/978-3-540-73325-6_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
eBook Packages: Computer ScienceComputer Science (R0)