Research on "Falling Rainfall" Recognition of Slag Transport System Based on Image Recognition Technology

As an important part of the power plant, the slag transfer system plays an important role in ensuring the safe, efficient and environmentally friendly operation of the power plant. The image processing technology can further improve the operation efficiency and reliability of the slag conveying system, and provide a strong guarantee for the sustainable development of the power plant. Based on the YOLOv5m algorithm, this paper improves the YOLOv5m algorithm through MobileNetV3 network and attention mechanism, and verifies the effectiveness of this algorithm by training and testing the photos of the slag transport system's historical records as a data set. The results show that the improved YOLOv5m algorithm has higher mean average accuracy, fewer parameters, faster real-time detection rate of "falling rainfall" exceeding the alarm value, and can effectively improve the work efficiency of the slag transport system, improve equipment utilization and operation efficiency, which is of great significance for the safe operation of the slag transport system.