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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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Based on the effects of stress wave propagation in larch (Larix gmelinii) wood, the propagation mechanism of stress wave was explored, and a theoretical model of the propagation velocity of stress waves in the three-dimensional space of wood was developed. The cross and longitudinal propagation velocities of stress wave were measured in larch wood under different moisture contents (46% to 87%, 56% to 96%, 20% to 62%, and 11% to 30%) in a laboratory setting. The relationships between the propagation velocity of stress waves and the direction angle or chord angle with different moisture contents were analyzed, and the three-dimensional regression models among four parameters were established. The analysis results indicated that under the same moisture content, stress wave velocity increased as the direction angle increased and decreased as chord angle increased, and the radial velocity was the largest. Under different moisture contents, stress wave velocity gradually decreased as moisture content increased, and the stress wave velocity was more noticeably affected by moisture content when moisture content was below the fiber saturation point (FSP, 30%). The nonlinear regression models of the direction angle, chord angle, moisture content, and the propagation velocity of stress wave fit the experiment data well (R2 ≥ 0.97).