A review of application of deep learning-based computer vision in tunnel lining defect detection
As an important supporting structure of the tunnel,it is very important to detect the diseases existing in the tunnel lining.However,the traditional tunnel defect detection methods are highly dependent on manual work,inefficient,and have certain safety risks.Therefore,how to efficiently and safely realize the automatic detection of defects has become one of the hot directions.Deep learning(DL)and computer vision(CV)are considered as promising methods for automatic detection of tunnel lining defects.In order to clarify the research and application of DL technology and CV technology in defect detection,the development history of tunnel lining defect detection technology was summarized.Based on the importance of data for DL model training,the establishment process of lining disease data set was summarized.Then,the method and application of DL-based CV technology in the detection of surface and internal diseases of tunnel lining were summarized.Finally,the problems existing in the current research were discussed,and the future development was prospected.
万方数据
维普
