The Impact of the Number of Sensors on Stress Wave Velocity in 2D Acoustic Tomography of Araucaria cunninghamii Sweet

This study investigated the effect of the number of sensors (8, 12, 16, and 20) on the measurement results of stress wave velocity in two-dimensional acoustic tomography of Hoop pine (Araucaria cunninghamii Sweet) trees and evaluated the method’s accuracy and operational efficiency in tree health diagnostics. Tests were conducted on five sample trees, two of which were confirmed to have internal damage using the drilling resistance method. The results showed that increasing the number of sensors improved image resolution and information completeness. However, differences in the average stress wave velocities among sensor configurations were not statistically significant (p ≥ 0.05), indicating limited overall velocity variation. In healthy trees, stress wave velocities measured with different sensor quantities (e.g., eight vs. twenty) exhibited weak linear correlations (R2 = 0.06–0.58), reflecting a relatively uniform internal structure. In contrast, damaged trees showed strong consistency in velocity results (R2 = 0.82–0.91, p < 0.01), with both minimum and average velocities being significantly lower than those in healthy trees. These findings demonstrate that acoustic tomography can effectively identify internal tree defects. Notably, even with only eight sensors, decay and cavities can still be accurately detected, which significantly enhances field inspection efficiency and reduces costs, thereby showing strong potential for practical applications.