LAUSR

The foreign object doped in the conveying belt is the most important factor to cause the tearing of the conveying belt. In order to solve the problem of low accuracy and poor real-time performance of foreign object detection, a new method based on improved Nanodet is proposed in this paper. The hardware of conveyor belt foreign object detection system is designed with ARM processor, and the system software is designed based on Android. It uses a conveyor belt foreign object detection system to detect foreign object. In order to detect foreign object images, a better Nanodet model is suggested. In order to increase detection accuracy while preserving processing speed, the model uses SIoU in place of the original position loss function. When the enhanced Nanodet model is applied to the conveyor belt foreign object detection system, the image of the foreign object appearing on the conveyor belt can be identified. The experimental findings indicate that a conveyor belt foreign object detection system based on an ARM processor and an Android operating system is capable of detecting foreign objects on conveyor belts with an average detection accuracy of 94.3%, a detection speed of 30 frames per second. The application of this method in the detection of foreign objects in conveyor belt can solve the shortcomings of existing methods. At the same time meet the requirements of the conveyor belt foreign object detection site environment.