Ontology type: schema:ScholarlyArticle
2003-08
AUTHORSJan Johansson, Olle Hagman, Bengt-Arne Fjellner
ABSTRACTThis study was carried out to investigate the possibility of calibrating a prediction model for the moisture content and density distribution of Scots pine (Pinus sylvestris) using microwave sensors. The material was initially of green moisture content and was thereafter dried in several steps to zero moisture content. At each step, all the pieces were weighed, scanned with a microwave sensor (Satimo 9,4 GHz), and computed tomography (CT)-scanned with a medical CT scanner (Siemens Somatom AR.T.). The output variables from the microwave sensor were used as predictors, and CT images that correlated with known moisture content were used as response variables. Multivariate models to predict average moisture content and density were calibrated using the partial least squares (PLS) regression. The models for average moisture content and density were applied at the pixel level, and the distribution was visualized. The results show that it is possible to predict both moisture content distribution and density distribution with high accuracy using microwave sensors. More... »
PAGES312-316
http://scigraph.springernature.com/pub.10.1007/s10086-002-0493-7
DOIhttp://dx.doi.org/10.1007/s10086-002-0493-7
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