Abstract:The long-time and high-speed running of an underground conveyor belt in a coal mine will consume a lot of electricity in the case of no coal or little coal. In order to reduce the electricity loss caused by the underground conveyor belts, we propose a no-load determination method of the conveyor belts combining the YOLOv3 algorithm with the edge-based structural similarity algorithm. First, the structure features and edge features are fused by the edge-based structural similarity algorithm. Then, the similarity of adjacent 10 frames of images is successively compared three times to judge the running state of a conveyor belt. If the conveyor belt is running, the YOLOv3 model based on the adaptive anchor box mechanism is used to detect the coal amount on the conveyor belt. Finally, whether the conveyor belt carries a load or not is judged. The experimental results show that the proposed method can effectively and accurately judge the no-load state of the conveyor belts and the detection accuracy reaches 96.85%.