Predicting the Strength of Sawn Products by X-ray Scanning of Logs: A Preliminary Study
Keywords:
Grading, modulus of elasticity (MOE), modulus of rupture (MOR), partial least squares (PLS), scanning, saw logs, X-rayAbstract
The aim of the study was to investigate the possibility of predicting the strength of centerboards from Norway spruce (Picea abies (L.) Karst.) saw logs, based on simulated X-ray LogScanner measurements. The study was based on eight logs. The logs were scanned using computed tomography (CT), four centerboards were sawn from each log, and the bending stiffness (MOE) and strength (MOR) of the boards were measured. The CT-images were used for simulations of the industrial X-ray LogScanner, resulting in simulated measurements of knot volume and the green density of heart-wood. Finally, multivariate models were calibrated using Partial Least Squares (PLS) regression. These models predict bending strength and stiffness based on the variables measured by the simulated X-ray LogScanner. Both bending strength and modulus of elasticity were defined as the mean value of the four boards from each log.
The results were very promising, with strong models for prediction of both MOR (R2 = 0.73) and MOE (R2 = 0.94) mean values for all four boards from each log. The results indicate that the X-ray LogScanner can be used for the sorting of saw logs according to strength and stiffness. The next step should be to repeat the study on a larger sample of material.
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