Detection of small cracks in large area cast in place concrete flooring construction based on YOLOv4algorithm

Due to the shrinkage of concrete materials and temperature effects, cracking of concrete floor structures is common in construction, which directly affects the stability of the foundation at the bottom of the floor. The traditional method for extracting crack structure features is relatively single, and there are errors in detecting small cracks in floor construction. Therefore, based on YOLOv4, a method for detecting small cracks in large-area cast-in-place concrete floor construction was studied. The deformation component of floor construction under temperature field was quantified, the crack information in the deformation component of large-area flooring was determined. Mean shift filtering was used to cluster small crack features, small cracks in concrete floors were detected based on YOLOv4 fusion of small features. The results showed that the proposed method could extract the characteristics of small cracks in concrete floors more comprehensively, with an accuracy of up to 98% in target detection of different types of cracks, and had practical value.