Influence of moisture content on estimating Young’s modulus of full-scale timber using stress wave velocity

Yamasaki, Mariko; Tsuzuki, Chika; Sasaki, Y.; Onishi, Yuji

doi:10.1007/s10086-017-1624-5

Cited by 22 publications

(16 citation statements)

References 11 publications

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“…It is important to detect wood internal defects which can endanger the health of trees. Different from other non-destructive testing technologies, such as X-ray [1][2][3], the stress wave method has become the mainstream technology in wood non-destructive testing because of its low cost, portability, and harmlessness [4][5][6]. So far, the wave propagation mechanism for standing trees or wood is not fully understood, and the precise physics model of sound's interaction with defect is very difficult to establish [7,8].…”

Section: Introductionmentioning

confidence: 99%

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Feng

et al. 2018

Applied Sciences

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In order to detect the size and shape of defects inside wood, an image reconstruction method based on segmented propagation rays of stress waves is proposed. The method uses sensors to obtain the stress wave velocity data by hanging around the timber equally, visualizes those data, and reconstructs the image of internal defects with the visualized propagation rays. The basis of the algorithm is precisely segmenting the rays to benefit the spatial interpolation. First, a ray segmentation algorithm using the elliptical neighborhood technique is proposed, which can be used to segment the rays and estimate the velocity values of segmented rays by the nearby original rays using elliptical zones. Second, a spatial interpolation algorithm utilizing a segmented ellipse according to the segmented rays is also proposed, which can be used to estimate the velocity value of a grid cell by the segmented ellipses corresponding to the nearby segmented rays. Then, the image of the internal defect inside the wood is reconstructed. Both simulation and experimental data were used to evaluate the proposed method, and the area and shape of the imaging results were analyzed. The comparison results show that the proposed method can produce high quality reconstructions with clear edges and high accuracy.

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Section: Introductionmentioning

confidence: 99%

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Feng

et al. 2018

Applied Sciences

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“…Maintaining wood above the fiber saturation point allowed mimicking the state of the matter in standing tree, while having the possibility to create controlled defects in the wood discs. It was reported that variation of moisture content above the fiber saturation point had an impact on the propagation of ultrasonic waves in wood (Sakai et al 1990;Unterwieser and Schickhofer 2011;Yamasaki et al 2017). The harvesting and the period of storage would have softened the gradient of moisture content within the Fig.…”

Section: Discussionmentioning

confidence: 98%

Ultrasound computed tomography on standing trees: accounting for wood anisotropy permits a more accurate detection of defects

Espinosa

Brancheriau

Cortes³

et al. 2020

Annals of Forest Science

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& 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.

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“…However, there was no similar correlation among different wood species, which might be due to the differences in the compositions. Yamasaki et al (2017) investigated the effect of moisture content on the stress wave propagation velocity and obtained the relationship between the moisture content and the rate of change of velocity of full-size timber. This relationship was used to estimate the Young's modulus of the timber in the air-drying state from the velocity in high-moisture condition.…”

Section: Introductionmentioning

confidence: 99%

Propagation velocity model and two-dimensional defect imaging of stress wave in larch (Larix gmelinii) wood

Wei

Sun

et al. 2021

BioRes

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The propagation law of stress wave in larch (Larix gmelinii) wood was studied in this work. External factors affecting the propagation velocity of stress wave in wood cross-section were studied using the orthogonal experiment method. The most influential factors were shown by the experimental results, and the parameters of the propagation velocity model of stress wave in larch wood were optimized. Based on the optimized propagation velocity model, combined with the traditional defect determination method, a twelve-directional stack imaging (TDSI) steps system was developed for larch wood internal defect detection. The analysis results showed that of the three external factors of temperature, moisture content, and illumination duration, temperature had the greatest influence on the propagation velocity model of stress wave in larch wood cross-section. Using TDSI to image the defective larch wood not only can locate the defective area, but also it can achieve a high imaging precision of 95.52%, and the imaging precision is unrelated to the location of the defect, which has a good quantitative defect detection effect.

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Influence of moisture content on estimating Young’s modulus of full-scale timber using stress wave velocity

Cited by 22 publications

References 11 publications

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Ultrasound computed tomography on standing trees: accounting for wood anisotropy permits a more accurate detection of defects

Propagation velocity model and two-dimensional defect imaging of stress wave in larch (Larix gmelinii) wood

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