Study on Nondestructive Detection Imaging Method of Log Knot Based on Judging the Shortest Path of Stress Wave Propagation

This paper presents an iterative stress wave log beam imaging algorithm based on external shape to predict the size, shape, and position of internal features in logs. The algorithm’s accuracy is analyzed to establish a theoretical and scientific basis for the prediction and evaluation of internal knots in standing trees. Six sample logs with natural knots were selected for study, and cross-sectional stress wave propagation tests were conducted using FAKOPP to collect data. Using the shortest propagation path method, the algorithm iteratively produced fault images of the log cross-sections. While the algorithm can roughly predict the location of internal features, discrepancies between predicted and actual shapes and sizes result in relative errors ranging from 15.66% to 52.08%. Except for sample log 6, the relative error for other logs is mostly within 31%, with logs 1, 2, and 5 showing errors under 20%. However, the imaging accuracy and effectiveness need improvement. Further experimental studies and algorithm enhancements are necessary to improve fault imaging and prediction accuracy, particularly in terms of shape and size precision.