Status Detection of Mine Air Door Based on Image Enhancement

Frequent accidents in coal mines have caused significant loss of lives and property. During coal mine production, it is crucial that the mine's air door remains securely closed at all times. However, under certain abnormal conditions, it poses a severe hazard to underground personnel if the mine air door unintentionally opens To enhance the accuracy of air door status detection across varying underground environments, this study introduces a novel joint image enhancement algorithm. Specifically, a joint image enhancement preprocessing method was developed using OpenCV to improve image quality. The processed images were then used to train an object detection model based on the YOLOv5 algorithm for 50 epochs to detect the air door's status. The resulting model achieved an accuracy of 94.1 %.