Development and Application of Intelligent Inspection Robot for Safety Hazards on Tailings Dam Surfaces
Timely detection of diseases such as slotting and gulch is the key to ensure the safety of tailings dam.Taking the tailings dam as the engineering background,an intelligent inspection robot for slotting and gulch on the tailings dam surface was developed by utilizing technologies such as tracked chassis systems and automation control.An improved network model YOLOv5m-ECA with convolutional block attention modules inserted into the YOLOv5m backbone network and neck network was proposed for the detection of dam surface diseases.Application research was conducted in unmanned inspection operations on tailings dam surfaces.The results show that the improved YOLOv5m-ECA algorithm improves the model's accuracy,mean average precision,and F1 score by 12 percentage points,6.1％,and 3.6 percentage points,respectively,compared to those before improvement.Compared with the performance of four mainstream object detection algorithms,YOLOv5m-ECA demonstrates stronger overall performance and is easily deployable on mobile detection equipment,making it more suitable for slotting and gulch detection on dam surfaces.Field applications have shown that this method can replace manual operations for unmanned inspection of tailings dam surfaces,providing an intelligent solution for rapid disease detection on dam surfaces.The detected disease positions correspond to the actual dam surface positions,demonstrating practical significance and application value.
Safety of tailings dam surfaceIntelligent inspectionResearch and development of robotSlotting identificationAttention mechanism
万方数据
维普
