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This paper is concerned with a technique for detecting and monitoring abnormal paper formation variations in machine direction online in various frequency regions. 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 time series block. The frequency content of each frequency region is characterized by a feature vector, which is transformed using the kernel 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 experimental investigations performed have shown good repetitiveness and stability of the paper formation abnormalities detection results. The tools developed are used for online paper formation monitoring in a paper mill.

A measurement platform for online studies of print runnability in a full-scale four-high web offset printing press is described. Results from two trial runs showed no effect of reel tightness on pr ...

This paper is concerned with the offset lithographic colour printing. To obtain high quality colour prints, given proportions of cyan (C), magenta (M), yellow (Y), and black (K) inks (four primary inks used in the printing process) should be accurately maintained in any area of the printed picture. To accomplish the task, the press operator needs to measure the printed result for assessing the proportions and use the measurement results to reduce the colour deviations. Specially designed colour bars are usually printed to enable the measurements. This paper presents an approach to estimate the proportions directly in colour pictures without using any dedicated areas. The proportions—the average amount of C, M, Y, and K inks in the area of interest—are estimated from the CCD colour camera RGB (L*a*b*) values recorded from that area. The local kernel ridge regression and the support vector regression are combined for obtaining the desired mapping L*a*b* ⇒ CMYK, which can be multi-valued.

A technique for measuring optical dot gain, i.e. the relative difference between the actual screen dot and the optically perceived one, is presented. By combining measurements from the non-optical nuclear microprobe with data from image analyzing technique the optical dot gain can be determined. The procedure to reach pixel by pixel correlation on a micrometer scale is discussed. In the newsprint sample studied in this investigation a typical optical dot gain between 15 and 20% was deduced. The variation in the optical dot gain was correlated with other characteristic parameters of the print and newsprint and especially a positive correlation to the mass density of the newsprint was observed.

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 paper is concerned with a multi-resolution tool for analysis of a time series aiming to detect abnormalities in various frequency regions. The task is treated as a kernel based novelty detection applied to a multi-level time series representation obtained from the discrete wavelet transform. Having a priori knowledge that the abnormalities manifest themselves in several frequency regions, a committee of detectors utilizing data dependent aggregation weights is build by combining outputs of detectors operating in those regions.

Fluorescence from paper following excitation by either ultraviolet or visible light gives information on the chemical composition of the paper. This can be used for on-line monitoring of the paper during production. Such measurements can be performed non-intrusively at sampling rates high enough to give a sub-millimetre resolution at paper webs moving at velocities higher than 20 metres per second. Two types of fluorescence meters, operating at different wavelengths, have been constructed. Together with an optical speedometer they have been tested at newsprint producing paper mills. A fluorescence based method for scanning cross-directional newsprint profiles in the laboratory has been developed. From these measurements the relative shrinkage of the paper during drying can be calculated using time-frequency analysis.

When water is removed from the paper during paper making, a dimensional change occurs in which the paper shrinks in the direction perpendicular to the direction of processing. The dimensional changes vary across the web and influence, e.g., the surface and compression properties of the paper; they also complicate the control of the paper machine. In this article, a robust method for estimating the relative shrinkage profile is presented. The method is based on a one-dimensional recording of the imprints from the forming fabric, using a fluorescence technique. The recording is transformed into a time-frequency spectrum, on which three different frequency estimators have been evaluated. In simulations on synthetic data and measurements on paper profiles the estimator that maximizes the correlation energy showed the most robust and accurate performance of the methods evaluated, even at a low signal-to-noise ratio.

A robust sensor is developed for on-line measurements in paper production. The sensor is designed for optimal response to lignin in paper. A diode laser operating at 630 nm is used for excitation a ...