The traditional crack detection method has the problems of large manpower,time consump-tion and low accuracy.Therefore,a crack detection method based on deep learning is proposed.By construct-ing and training the YOLOv7 deep neural network model and using a large number of coal sample image da-ta,the automatic identification of cracks in coal samples is realized.The experimental results show that the YOLOv7 model has achieved high accuracy and robustness in crack detection,and has a good application prospect.The research results are expected to provide an efficient and accurate crack detection solution for the coal mine industry,and provide strong support for the safety management and quality evaluation of coal production.
关键词
深度学习/YOLOv7/目标检测/裂隙识别
Key words
deep learning/YOLOv7/object detection/identification of cracks
维普
万方数据