A Stress Wave Tomography Algorithm for Detecting Holes in Wood using YOLOv5 and Constrained Contour
In this study,we proposed a stress wave tomography algorithm based on YOLOv5 and constrained contour for detecting holes in wood.This method ensures the quality of images with reduced number of sensors.Firstly,virtual defect images generated by simulation software were used as samples for training.Next the position of the defect was accurately detected through the YOLOv5 model.Then,the proposed constrained contour algorithm was used to perform global and local constraints on the detection results,to reconstruct the contour of the defect,and to obtain the final images.Experiment results showed that the average accuracy of this method was 94.73%.When the number of stress wave sensors was reduced from 12 to 6,the defect images reconstructed by this method had higher precision and clearer defect edges than traditional imaging methods,with an average precision improvement of 38.76%.
国家科技期刊平台
NSTL
万方数据
维普
