Research on Identification of Loaded Crack of Coal Samples Based on YOLOv7
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.
deep learningYOLOv7object detectionidentification of cracks
万方数据
维普
