Ultrasound computed tomography on standing trees: accounting for wood anisotropy permits a more accurate detection of de
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RESEARCH PAPER
Ultrasound computed tomography on standing trees: accounting for wood anisotropy permits a more accurate detection of defects Luis Espinosa 1,2
&
Loïc Brancheriau 2 & Yolima Cortes 3 & Flavio Prieto 1 & Philippe Lasaygues 4
Received: 4 December 2019 / Accepted: 9 June 2020 # INRAE and Springer-Verlag France SAS, part of Springer Nature 2020
Abstract & Key message Considering anisotropy in image reconstruction algorithm for ultrasound computed tomography of trees resulted in a more accurate detection of defects compared to common approaches used. & Context Ultrasound computed tomography is a suitable tool for nondestructive evaluation of standing trees. Until now, to simplify the image reconstruction process, the transverse cross-section of trees has been considered as quasi-isotropic and therefore limiting the defect identification capability. & Aims An approach to solve the inverse problem for tree imaging is presented, using an ultrasound-based method (travel-time computed tomography) suited to the anisotropy of wood material and validated experimentally. & Methods The proposed iterative method focused on finding a polynomial approximation of the slowness in each pixel of the image depending on the angle of propagation, modifying the curved trajectories by means of a raytracing method. This method allowed a mapping of specific elastic constants using nonlinear regression. Experimental validation was performed using sections of green wood from a pine tree (Pinus pinea L.), with configurations that include a healthy case, a centered, and an off-centered defect. & Results Images obtained using the proposed method led to a more accurate location of the defects compared to the filtered backprojection algorithm (isotropic hypothesis), considered as reference. & Conclusion The performed experiments demonstrated that considering the wood anisotropy in the imaging process led to a better defect detection compared to the use of a common imaging technique. Handling Editor: Jean-Michel Leban Contributions of the co-authors Luis Espinosa: conceptualization and definition of the methodology, performing the experimental tests, running the data analysis, and writing the manuscript. Loïc Brancheriau: conceptualization and definition of the methodology, supervising the work, coordinating the research project, contribution to the analysis and discussion, and writing the manuscript. Yolima Cortes: contribution to the analysis and discussion. Flavio Prieto: conceptualization and definition of the methodology, supervising the work, coordinating the research project, and revising the manuscript. Philippe Lasaygues: contribution to the analysis and discussion and revising the manuscript. * Luis Espinosa [email protected]
1
Dept. of Mechanical and Mechatronics Engineering, Universidad Nacional de Colombia, Carrera 45 N°26-85, Bogotá, Colombia
Loïc Brancheriau [email protected]
2
CIRAD, UR BioWooEB, Univ Montpellier, 73 Rue J.F. Breton, Montpellier, France
3
Agencia de Renovación del Territorio, Ca
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