Intelligent Detection Method of Coal Transport Train Carriage Status Based on Machine Vision
This paper proposes an intelligent detection method based on machine vision for the state of coal transport trains,which can detect and warn potential safety hazards in time,improve inspection efficiency,effectively prevent accidents,and ensure the safety of coal transport.Using linear array camera and other equipment to collect the original images of coal transport train cars.The Retinex algorithm is used to enhance the original image of the train car and improve the image quality.Sobel operator is applied to the segmentation of the carriages in the image,and the complete picture of each carriage is obtained,which is used for the subsequent state detection of the carriage.The YOLOv5 algorithm model is constructed,and a method to suppress heterogeneous redundant frames is proposed,which is improved.The improved model is used to complete intelligent state detection of coal transport train cars,and the detection results are applied to abnormal alarm of train cars.Experiments show that this method can accurately detect the status of coal transport train cars and send alarm information in time,and has a good performance in mAP and FPS.