Research and Design of Belt Deviation Detection System Based on Single-side Rollers.

Belt conveyors often work in more complex environments, although many are indoors. However, due to the structure of the plant and other reasons, it is difficult to install the camera directly above the belt when using the camera to monitor the belt or identify faults. At this time, the staff can only find a location as far as possible can play a role in monitoring the belt conveyor to install the camera. In this case it is more difficult to analyze whether the belt is running away. On the other hand, the previous belt deflection detection method is through the artificial delineation of the standard position of the belt, the actual position of the belt and the standard position for comparison, which to a large extent there are human factors interference, resulting in the detection results are not precise enough. Therefore, in this paper, for the belt that can only monitor the type of unilateral rollers, we propose a method to recognize whether the belt is empty or not, and then determine the standard position of the belt through a multi-task learning model with joint target detection and semantic segmentation. This enables adaptive recognition of the standard position of the belt. The degree and direction of belt deflection is determined by obtaining the line connecting the straight line at the edge of the belt and the uppermost corner point of the rollers. The overall accuracy of the system is 94.9%, which is obtained by experimenting with the multi-task learning model and the belt runout judgment model respectively. It can be concluded that the belt runout detection method proposed in this paper can be a good solution to the situation where the camera installation position is not ideal. It reduces the failure rate of the belt conveyor and provides a guarantee for the normal operation of the belt conveyor. [ABSTRACT FROM AUTHOR]