Bridge Crack Detection System Design

Aiming at the low efficiency of traditional bridge crack detection and the problem of certain safety factors, this paper designs a bridge crack detection system based on machine learning. The system firstly carries out crack data collection and pre-processing, crack processing, classification and then crack parameter measurement, and finally integrates all the above steps into the GUI software interface. The whole system realizes the detection of bridge cracks and the display of parameters, and also gives the health condition of the bridge and suggestions. The design not only improves the efficiency of bridge crack detection, but also lays a good research foundation for practical engineering applications.