Detecting internal defects in woods using intersection fitting

Wood defects have significantly jeopardized the health of trees in the utility value of timber, leading to an immeasurable impact on ancient and venerable trees. Therefore, non-destructive testing (NDT) technology can play a crucial role in the efficient utilization of timber and the conservation of heritage trees. Among them, stress wave testing has been widely applied in recent years, due to its safety, portability, and adaptability to complex environments. However, the conventional stress wave NDT can often fail to consider the influence of wood anisotropy on wave propagation, thereby limiting the imaging accuracy and effectiveness in the detection of internal defects in tree trunks. Furthermore, stress wave data can be collected to uniformly distribute several sensors along the cross-section of the tree under test, in order to accurately map actual cavities. There is also some mismatch between the initial stress wave data visualization and the actual situation in the tree cross-section, due to the uneven speed of stress wave propagation that is caused by wood anisotropy. In this study, an approach was proposed to correct the collected stress wave velocity, and then normalize the corrected velocity using deviation rates. The imaging area was subdivided into multiple grid cells. The speed function of each stress wave ray was refitted, according to the intersection speeds of the rays. A stress wave propagation ray diagram was then drawn using the fitted ray speeds. The speeds of each grid cell were calculated in the imaging area. The nearest neighbor interpolation was used to realize some cells without data. Defect status was determined using the grid cell speeds. The internal defect images of the tree were reconstructed using image processing techniques. Five log samples were tested with the proportion of the defect area after image segmentation and the degree of overlap with the defect shape as evaluation criteria. The results indicate that the imaging algorithm achieved an overall average relative error, accuracy, precision, and recall rate of 8.25%, 93.19%, 80.37%, and 82.30%, respectively. The positions and sizes of defect areas were more consistent with the actual situation. The wave speed model improved the data processing of traditional ones. The robustness against crack interference was also enhanced to identify the crack regions. The findings can greatly contribute to the efficient utilization of timber. A theoretical basis can also provide for the conservation of heritage trees. However, some limitations still remained to detect the micro-cracks and decay on the tomography imaging using intersection fitting, indicating some improvement and optimization. Future research efforts can focus primarily on the robustness and imaging accuracy of tomography imaging using intersection fitting. A solid foundation can also be laid to develop three-dimensional imaging technology.