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Defect detection in lumber including knots using bending deflection curve: comparison between experimental analysis and finite element modeling

Abstract

A new method has been developed for detecting localized defects such as edge knots using a bending deflection curve. The coordinates of a bottom edge (edgeline) of an unloaded piece of lumber are extracted from a digital image, and a bending deflection curve is obtained from the displacement of the edgeline of the lumber using a digital image correlation (DIC) technique. Depending on the knots within the beam, the bending deflection curve is shifted from the curve of a defect-free beam. The measured bending deflection curve is regressed to a theoretical curve by elementary beam theory. A finite element method (FEM) model of the beams including defects as simplified knot structure has been performed. Comparison between the bending experiment and FEM analysis shows that cross-sectional reductions cause characteristic variations in the bending deflection curves depending on the position of encased knots, and local grain distortions cause variations in the curves depending on the direction of spike knots. Using the residual variance between the measured deflection curve and a polynomial regression curve, it is possible to detect knots at which failures initiate.

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Correspondence to Hiroaki Nagai.

Additional information

Part of this article was presented at the 57th Annual Meeting of the Japan Wood Research Society, Hiroshima, Japan, August 2007

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Nagai, H., Murata, K. & Nakano, T. Defect detection in lumber including knots using bending deflection curve: comparison between experimental analysis and finite element modeling. J Wood Sci 55, 169–174 (2009). https://doi.org/10.1007/s10086-008-1016-y

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Key words

  • Bending deflection curve
  • Defect detection
  • Knot
  • Digital image correlation