Application Research of YOLOv5 Algorithm in Intelligent Recognition of Apparent Defects in Concrete Bridges
With the rapid development of transportation construction in China,the surge in the number of bridges,the regular inspection business has become increasingly heavy.The detection of bridge surface defects mainly relies on manual visual inspection and simple tool detection,which is inefficient,labor-intensive,and greatly affected by environmental and human subjective factors.In order to improve the detection quality and efficiency,reduce the cost of manual labor,the YOLOv5 algorithm's object detection method is adopted to analyze the intelligent recognition of concrete bridge surface defects(peeling,exposed steel bars,hollows,etc.)and verify through quantitative real detection data.The results show that:1)Compared with other methods,the object recognition detection method using the YOLOv5 algorithm has a recognition rate increased by 4 times,which can identify common concrete surface defects faster.When the IoU threshold is 0.5,the mAP detection accuracy value reaches to 72.5%,which is significantly higher than other methods;2)The YOLOv5 algorithm applied to concrete bridge surface defect detection can meet the needs of fast and accurate defect detection and defect detection in real time,and can be used for the detection of the appearance of bridges,tunnels,roads and buildings.
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