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Journal of Wood Science

, Volume 63, Issue 6, pp 615–624 | Cite as

Residual strain analysis with digital image correlation method for subsurface damage evaluation of hinoki (Chamaecyparis obtusa) finished by slow-speed orthogonal cutting

  • Yosuke Matsuda
  • Yuko Fujiwara
  • Koji Murata
  • Yoshihisa Fujii
Original article

Abstract

A digital image correlation (DIC) method was applied to measure strain which arose and remained beneath the finished surface in slow-speed orthogonal cutting of hinoki (Chamaecyparis obtusa), to evaluate the damage in the subsurface cell layers. While the quarter-sawn surface was cut parallel to the grain, the side surface, flat-sawn surface, was captured by a high-speed camera. The images were analyzed to calculate strain in a region of 0.67 × 0.22 mm allocated beneath the finished surface. Almost no strain normal to the cutting direction was detected for the depth of cut and cutting angles, 0.05 mm and smaller than 60°, respectively. For the depths of cut and cutting angles, larger than 0.1 mm and smaller than 60°, respectively, the fore-split induced tensile strain normal to the cutting direction, although it hardly remained after the cutting. The compression strain normal to the cutting direction clearly remained for the cutting angles larger than 70°, regardless of the depths of cut employed in this study. The subsurface damage assumed from the residual strain distribution corresponded to the appearance of the subsurface layer in the X-ray computed tomography (CT) images. It was also revealed, and the DIC program could not always measure excessively large strain correctly.

Keywords

Orthogonal cutting Digital image correlation Residual strain 

Notes

Acknowledgements

This research was supported by research Grant #201426 of Forestry and Forest Products Research Institute. Authors would like to express sincere thanks to Kanefusa Corporation for providing the cutting tools and to Food Research Institute (NARO) for the X-ray CT system.

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Copyright information

© The Japan Wood Research Society 2017

Authors and Affiliations

  1. 1.Forestry and Forest Products Research InstituteTsukubaJapan
  2. 2.Graduate School of AgricultureKyoto UniversityKyotoJapan

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