Wear Detection of Tank Road Wood in Underground Mine Hoisting System Based on YOLOv7
Cannel logs are generally used to fix the mine hoisting device after it stops,how to detect the wear of the cannel logs is of great significance to ensure the stable operation of the hoisting device as well as to ensure the normal production of underground mines.The YOLOv7 algorithm performs well in the target detection task,which is suitable for the special working environment of mines.In this paper,the proposed cannel wood wear detection algorithm model through the camera continuous acquisition of cannel wood wear change pictures,and then based on the YOLOv7 algorithm for training,after obtaining the training model,detection and identification of cannel wood wear pictures and make an evaluation of the accuracy of the algorithm model.The Loss value of the cannel wood dataset after the model training is finally reduced to 0.804,and the mAP value reflecting the detection effect of the dataset reaches 0.938.The results show that the cannel wood wear detection algorithm can overcome the harsh environment of the underground to detect the wear of the cannel wood and can effectively improve the efficiency of the inspectors and ensure the safety of the hoisting device in the mine.
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