Abstract

Strain measurement is critical for wood quality evaluation. Using conventional strain gauges constantly is high cost, also challenging to measure precious wood materials due to the use of strong adhesive. This study demonstrates the correlation between the light scattering degrees inside the wood during tension testing and their macroscopic strain values. A multifiber-based visible-near-infrared (Vis–NIR) spatially resolved spectroscopy (SRS) system was designed to rapidly and conveniently acquire such light scattering changes. For the preliminary experiment, samples with different thicknesses, from 2 to 5 mm, were measured to evaluate the influence of sample thickness. The differences in Vis–NIR SRS spectral data diminished with an increase in sample thickness, suggesting that the SRS method can successfully measure the wood samples' whole strain (i.e., surface and inside). Then, for the primary experiment, 18 wood samples were each prepared with approximately the same sample thickness of 2 mm and 5 mm to construct strain calibration models, respectively. The prediction accuracy of the 2-mm samples was characterized by a determination coefficient (R2) of 0.81 with a root mean squared error (RMSE) of 343.54 με for leave-one-out cross-validation; for test validation, the validation accuracy was characterized by an R2 of 0.76 and an RMSE of 395.35 με. For the validation accuracy of the 5-mm samples, R2val was 0.69 with 440.78 με RMSEval. Overall, the presented calibration results of the SRS approach were confirmed to be superior to the standard diffuse reflectance spectroscopy.

Highlights

  • Wood is a natural material with multi-layered elongated cells

  • This paper reports on wood strain prediction results obtained by evaluating the changes in Vis–NIR SRS spectral data collected from wood samples during tension testing

  • The objectives of this paper are as follows: (1) design a multifiber-based Vis–NIR SRS system to rapidly and nondestructively acquire light scattering characteristics; (2) examine the relationship between SRS signals and wood tension strains by principal component analysis (PCA); and (3) construct wood strain calibration models by partial least squares (PLS) regression

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Summary

Introduction

Wood is a natural material with multi-layered elongated cells. The wood cell wall is a macromolecular composite formed of cellulose, hemicelluloses, and lignin (Hon and Chang 1984). Hemicelluloses function as a coupling agent to hold the cellulose (Burgert 2006). The conventional method for wood strain measurement is to use a strain gauge, which is high cost (either disposable or reusable ones) in constant use (Yang et al 2005). The heritage community generally does not allow the application of strain gauges on wooden arts (Anaf et al 2020). Difficulties arise when strain gauges are used in an environment where the electromagnetic wave interference is extensive (Liu et al 2015; Barr et al 2017)

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