Abstract
A novel method for estimating the wood moisture content above the fiber saturation point (FSP) is proposed, and the method performance is confirmed. Previous studies have highlighted that there is a negative linear correlation between the specific dynamic Young’s modulus (log (E/ρ)) and tangent loss (log (tanδ)) of clear small wood specimens. We confirm that this correlation can be obtained for air-dried commercial lumber from Japanese cedar, or sugi (Cryptomeria japonica), via experimental analysis. The best-fit linear regression line of this correlation only changes by the apparent density above the FSP (i.e., only by the moisture content of the specimen) when E and tanδ are kept constant in this high moisture content range. Here, we derive an equation to calculate the moisture content using log (E/ρ) and log (tanδ) based on the regression line of sugi wood at the FSP. A 45-day drying test was conducted on 23 green lumber specimens, with the E/ρ and tanδ values calculated from the natural resonance frequency fr, the logarithmic decrement λ and dimensions at various drying stages. The estimated moisture contents are in good agreement with the measured values, confirming the performance of proposed moisture content method.
Highlights
Non-destructive and practical methods for estimating the moisture content of green wood and wood during the drying process are important
Influence of defects on the correlation between the specific dynamic Young’s modulus and tangent loss Figure 2 shows the correlation between log (E/ρ) and log for the Group A specimens, which exhibits a linear regression with a correlation coefficient of 0.96
The moisture content could be estimated with high accuracy using our proposed method
Summary
Non-destructive and practical methods for estimating the moisture content of green wood and wood during the drying process are important. Popular methods involve moisture meters that employ electric capacitance or electrical resistance, but these instruments are not good at measuring the moisture content above the FSP. Guan et al [11] tried to estimate the moisture content of lumber using these characteristics, but a correction that used values before the drying process was necessary to eliminate the influence of inherent variations in the mechanical properties of the wood specimens. Guan et al [13, 14] estimated the moisture content gradient in lumber using the ratio of the natural frequencies for several vibration modes. Aratake et al [15] estimated the moisture content using the ratio of the natural frequencies for higher vibration modes to those at the initial stage of drying to avoid influences from the inherent variations in the mechanical properties of the wood specimens. Tsutsumi et al [19] predicted the average moisture content precisely using statistical models based on the vibrational spectra
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