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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 indicated that increasing the number of sensors improved image resolution and information completeness. However, differences in average stress wave velocities among sensor configurations were not statistically significant (p ≥ 0.05), indicating limited variation overall. In healthy trees, stress wave velocities measured under different sensor quantities (e.g., 8 vs. 20) exhibited weak linear correlations (R2 = 0.06–0.58), reflecting relatively uniform internal structures. In contrast, damaged trees showed strong consistency in velocity results (R2 = 0.82–0.91, p < 0.01), and both minimum and average velocities were significantly lower than in healthy trees. These findings demonstrate that acoustic tomography can effectively identify internal tree defects. Even with only eight sensors, decay and cavities can still be accurately detected, enhancing field inspection efficiency and reducing costs, thus showing strong potential for practical applications.