Infrared and Laser Engineering, Volume. 53, Issue 7, 20240176(2024)
Detection method for structural defects of railway clip fastener based on 3D line laser sensor
[1] MARINO F, DISTANTE A, MAZZEO P L et al. A real-time visual inspection system for railway maintenance: Automatic hexagonal-headed bolts detection[J]. IEEE Transactions on Systems Man & Cybernetics Part C, 37, 418-428(2007).
[2] [2] XIA Y, XIE F, JIANG Z. Broken railway fastener detection based on adaboost algithm[C]2010 International Conference on Optoelectronics & Image Processing, 2010: 313316.
[3] FENG H, JIANG Z, XIE F et al. Automatic fastener classification and defect detection in vision-based railway inspection systems[J]. IEEE Transactions on Instrumentation & Measurement, 63, 877-888(2014).
[4] WANG L, ZHANG B, WU J et al. Computer vision system for detecting the loss of rail fastening nuts based on kernel two-dimensional principal component – two-dimensional principal component analysis and a support vector machine[J]. Rail & Rapid Transit, 230, 1842-1850(2016).
[5] [5] GIBERT X, PATEL V M, CHELLAPPA R. Robust fastener detection f autonomous visual railway track inspection [C]2015 IEEE Winter Conference on Applications of Computer Vision, 2015: 694701.
[6] WANG Qiang, LI Bailin, HOU Yun et al. An improved LBP feature for fastener identification[J]. Journal of Southwest JiaoTong University, 53, 893-899(2018).
[8] LUO Jianqiao, LIU Jiajia, LI Bailin et al. Detection for railway fasteners based on local features and semantic information[J]. Application Research of Computers, 33, 2514-2518,2523(2016).
[9] WEI X, YANG Z, LIU Y et al. Railway track fastener defect detection based on image processing and deep learning techniques: A comparative study[J]. Engineering Applications of Artificial Intelligence, 80, 66-81(2019).
[10] XU Guiyang, LI Jinyang, BAI Tangbo et al. Detection method of track fastener state based on improved mask R-CNN[J]. China Railway Science, 43, 44-51(2022).
[11] BAI T, YANG J, XU G et al. An optimized railway fastener detection method based on modified faster R-CNN[J]. Measurement, 182, 109742(2021).
[12] [12] SHI Gongbiao. Research on 3D Visual Inspection of Metro Rail Fasteners [M]. Nanjing: Southeast University, 2021: 193. (in Chinese)
[16] GAO Hong, WANG Yong, TANG Chao et al. Track fastener detection method based on decision tree classification and region growth[J]. Bulletin of Surveying and Mapping Bull Surv Map, 2022, 18-22(2022).
[17] WANG Le, ZHOU Qian, FANG Yue et al. Detection method of rail fastener fastening state based on line structured light[J]. Laser & Optoelectronics Progress, 58, 1612002(2021).
[18] MAO Q Z, CUI H, HU Q W et al. A rigorous fastener inspection approach for high-speed railway from structured light sensors[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 143, 249-267(2018).
[19] [19] CUI Hao. Research on key technologies of service status detection of track fasteners based on structured light point cloud [D]. Wuhan: Wuhan University, 2019: 1132. (in Chinese)
[21] NIU Zhiyou, SHEN Bosheng, LU Kaixin et al. Research on measurement method of material storage capacity of silo based on laser radar scanning[J]. Journal of Huazhong Agricultural University, 43, 293-301(2024).
[22] [22] QI C R, YI L, SU H, et al. Point++: deep hierarchical feature learning on point sets in a metric space [C]Proceedings of the 31st International Conference on Neural Infmation Processing Systems (NIPS''17), 2017, 30: 51055114.
[23] [23] SATO M, BITTER I, BENDER M A, et al. TEASAR: Treestructure extraction algithm f accurate robust skeletons [C]Proceedings the Eighth Pacific Conference on Computer Graphics Applications, 2000, 449: 281287.
[24] DEY T K. Curve and surface reconstruction -algorithms with mathematical analysis[J]. Mathematics Today, 44-52(2008).
[25] MARAGOS P A, SCHAFER R W. Morphological skeleton representation and coding of binary images[J]. Acoustics Speech & Signal Processing IEEE Transactions on, 34, 1228-1244(1986).
[26] [26] CAO J, TAGLIASACCHI A, OLSON M, et al. Point cloud skeletons via laplacian based contraction [C]2010 Shape Modeling International Conference, 2010: 187197.
[28] HAO Ruqian, ZHOU Xiangzhou, ZHANG Jing et al. An automatic object detection method for microscopic images based on attention mechanism[J]. Opto-Electronic Engineering, 49, 46-56(2022).
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Xiaocui YUAN, Yongtao WANG, Baoling LIU, Dibo HOU, Zonghui JIANG. Detection method for structural defects of railway clip fastener based on 3D line laser sensor[J]. Infrared and Laser Engineering, 2024, 53(7): 20240176
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Received: Apr. 22, 2024
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Published Online: Aug. 9, 2024
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