[1] [1] NI Y,ZHANG Q,XIN R.Magnetic flux detection and identification of bridge cable metal area loss damage[J].Measurement,2021,167:108443.

[4] [4] WANG Z,HE B,ZHOU Y,et al.Design and implementation of a cable inspection robot for cable-stayed bridges[J].Robotica,2021,39(8):1417-1433.

[5] [5] LI X,GAO C,GUO Y,et al.Cable surface damage detection in cable-stayed bridges using optical techniques and image mosaicking[J].Optics & Laser Technology,2019,110:36-43.

[6] [6] WEI Y,XU G,LIU H,et al.OpenCV-based 3D printing physical surface defect detection［C］//IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), December 20-22,2019,Chengdu,China.New York:IEEE,2019,1:1924-1927.

[7] [7] FU L,ZHANG S,GONG Y,et al.Medicine glass bottle defect detection based on machine vision［C］//IEEE Chinese Control and Decision Conference (CCDC),June 3-5,2019,Nanchang,China.New York:IEEE,2019:5681-5685.

[8] [8] XING J,YANG P,QINGGE L T.Robust 2D Otsu′s algorithm for uneven illumination image segmentation[J].Computational Intelligence and Neuroscience,2020,2020(3):1-14.

[10] [10] HOU S,DONG B,WANG H,et al.Inspection of surface defects on stay cables using a robot and transfer learning[J].Automation in Construction,2020,119:103382.

[11] [11] LI K,WANG X,JI L.Application of multi-scale feature fusion and deep learning in detection of steel strip surface defect［C］//IEEE Artificial Intelligence and Advanced Manufacturing Conference (AIAM),October 16-18,2019,Dublin,Ireland.New York:IEEE,2019:656-661.

[12] [12] LI D,CONG A,GUO S.Sewer damage detection from imbalanced CCTV inspection data using deep convolutional neural networks with hierarchical classification[J].Automation in Construction,2019,101:199-208.

[15] [15] LIU S,QI L,QIN H,et al.Path aggregation network for instance segmentation［C］//IEEE Computer Vision and Pattern Recognition Conference,June 18-23,2018,Salt Lake City,UT,USA.New York:IEEE,2018:8759-8768.

[17] [17] PAN G,ZHENG Y,GUO S,et al.Automatic sewer pipe defect semantic segmentation based on improved U-Net[J].Automation in Construction,2020,119:103383.

[20] [20] DONG K,ZHOU C,RUAN Y,et al.MobileNetV2 model for image classification［C］//IEEE Information Technology and Computer Application Conference (ITCA),December 18-20, 2020,Guangzhou,China.New York:IEEE,2020:476-480.