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SUMMARY:This review covers the effect of mechanical pre-treatment of wood chips on the energy consumption in refining and the quality of pulp. To understand the mechanisms of mechanical pre-treatment, a short description of relevant refining theory and reported effects of pre-treatment on wood morphology is given. Mechanical pre-treatment offers a chance to utilize the energy needed to defibrate chips in a more efficient way, minimizing the cyclic elastic deformations which are the main defibration mechanism in refining. Studies of fibre morphology indicate that compressive pretreatment mechanically introduces favorable weak points in the S1 and S2 fibre walls where defibration proceeds easier upon subsequent refining.Published results which cover the effect of the pretreatment on energy consumption and pulp properties are reviewed. Energy reduction of between 10% and 30% is reported in the literature. High ratio of volumetric compression is necessary. Pressurized conditions are required to ensure that the fibres are not damaged during the pre-treatment. Other effects of compressive pretreatment include a more uniform chip size and moisture content, better penetration of chemicals and removal of extractives from the chips. A list of equipment used for chip pre-compression is provided together with published results of pilot-scale and mill-scale operation.
SUMMARY: Thermo-Mechanical Pulp (TMP) refiners served in this work as an example of how to combine oversampled and undersampled variables on a common timeframe for further analysis.To get more information from the refining process, temperature measurement arrays in the refining zones were studied alongside process measurements such as motor load, production rates, plate gaps, dilution waters, pulp properties and manually measured blow-line consistency.The undersampled data set consisted of 63 laboratory samples obtained at a Swedish TMP mill, which were tested for tensile index, mean fiber length and Somerville shives content. The pulp samples were obtained at five different periods during three months to cover a large dynamic operating window.The data set was expanded using a piece-wise linear approach. The measurements inside the refining zone were shown to be important variables when interlacing the undersampled pulp properties with the oversampled process data set, consisting of 350 000 samples.Use of an extended entropy model provided a palette of information about the process conditions inside the refining zone. Particularly, the residence time and the consistency in the refining zones were essential for the pulp property development, as a link between the refining segment pattern used and the current state of refiner operation. During the latest decade, the trend in pulp and paper has been to connect traditional measurement devices and distributed control applications with mill-wide systems to provide databases for deeper process analysis. Such applications produce a data deluge that severely stresses the available analog-to-digital converters and communication bandwidth. As a consequence, important theoretical efforts have been performed to create soft sensors, under different low-dimensional empirical and physical modeling frameworks directly in the process computers, see e.g. Karlström and Eriksson (2014a,b). These approaches have also enabled the development of new measurement systems and methods for information extraction that often set limits on the digital storage resources. In many cases this is handled by decimating (filtering and downsampling) the signals already in the distributed control algorithms. Since downsampling reduces the sampling rate, some important information can be lost for future analysis if the Nyquist-Shannon sampling theorem is not maintained, see Nyquist (1928), Shannon (1949) and Jerri (1977). ADDRESSES OF THE AUTHORSEven when the decimation is performed properly, the process computers still provide a huge amount of information. This information contains both oversampled and undersampled variables in many cases, i.e. oversampled process data provided at a higher sampling rate compared with undersampled variables such as pulp property analysis from laboratory tests. The latter can be seen as data residing in a much lower dimensional space. Undersampled data sets are most often obtained with non-equidistant sampling intervals while the process variables from the distributed c...
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