Identification of segment joint and automatic segmentation for shield tunnel based on LiDAR detection

被引:1
作者
Shen, Shui-Long [1 ]
Zhang, Jia-Xuan [2 ]
Chen, Yu-Lin [3 ]
Zhou, Annan [4 ]
机构
[1] Shantou Univ, Coll Engn, Guangdong Engn Res Ctr Smart Construct & Maintenan, Shantou 515063, Guangdong, Peoples R China
[2] China Construct Eighth Engn Div Corp LTD, Shanghai 200122, Peoples R China
[3] Shanghai Jiao Tong Univ, Sch Ocean & Civil Engn, Dept Civil Engn, Shanghai 200240, Peoples R China
[4] RMIT Univ, Sch Engn, Discipline Civil & Infrastruct Engn, Melbourne, Vic 3001, Australia
关键词
Joint identification; Shield tunnel; Automatic segmentation; LiDAR data;
D O I
10.1016/j.tust.2025.106758
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study presents a novel method for identifying joints and automatically segmenting shield tunnels using light detection and ranging (LiDAR). In cylindrical coordinates, the Hough transform is used to extract feature LiDAR data corresponding to ring joints at different azimuths. This feature extraction using LiDAR data facilitates the computation of ring joint feature coordinates and average ring joint width. Subsequently, the M-estimator Sample Consensus (MSAC) algorithm is used to fit the plane containing the ring joint, resulting in successful recognition and segmentation of ring joints within the tunnel LiDAR data. Following the segmentation of the LiDAR data into distinct ring LiDAR data, the three-sigma (3 sigma) criterion is used to extract coordinates of longitudinal joint endpoints. The average width of the longitudinal joints is then determined. In cases where extraction of the longitudinal joint points is challenging, the azimuth difference in the design model is leveraged to calculate the azimuths. This approach enables joint recognition within LiDAR data as well as the geometric segmentation of individual segments. The proposed method is validated using a case study from Luoyang Metro Line 2. The results indicate that the segmentation method can accurately extract the majority of the ring and longitudinal joints. Moreover, these results are useful for not only monitoring structural health but also developing a building information model (BIM) for the tunnel.
引用
收藏
页数:13
相关论文
共 36 条
[1]  
Arshi O, 2023, Smart Construction and Sustainable Cities, V1, DOI [10.1007/s44268-023-00022-2, 10.1007/s44268-023-00022-2, DOI 10.1007/S44268-023-00022-2]
[2]   GENERALIZING THE HOUGH TRANSFORM TO DETECT ARBITRARY SHAPES [J].
BALLARD, DH .
PATTERN RECOGNITION, 1981, 13 (02) :111-122
[3]   Aerial LiDAR Data Augmentation for Direct Point-Cloud Visualisation [J].
Bohak, Ciril ;
Slemenik, Matej ;
Kordez, Jaka ;
Marolt, Matija .
SENSORS, 2020, 20 (07)
[4]  
Chen Y., 2024, MethodsX
[5]   3D model-based terrestrial laser scanning (TLS) observation network planning for large-scale building facades [J].
Chen, Zhiping ;
Zhang, Wendian ;
Huang, Ronggang ;
Dong, Zhen ;
Chen, Chi ;
Jiang, Liming ;
Wang, Hansheng .
AUTOMATION IN CONSTRUCTION, 2022, 144
[6]   BIM-based task-level planning for robotic brick assembly through image-based 3D modeling [J].
Ding, Lieyun ;
Jiang, Weiguang ;
Zhou, Ying ;
Zhou, Cheng ;
Liu, Sheng .
ADVANCED ENGINEERING INFORMATICS, 2020, 43
[7]   Real-time deformation monitoring of large diameter shield tunnel based on multi-sensor data fusion technique [J].
Ding, Ning ;
Zhou, Yuliang ;
Li, Dongpeng ;
Zeng, Kun .
MEASUREMENT, 2024, 225
[8]   Dislocation Detection of Shield Tunnel Based on Dense Cross-Sectional Point Clouds [J].
Du, Liming ;
Zhong, Ruofei ;
Sun, Haili ;
Pang, Yong ;
Mo, You .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (11) :22227-22243
[9]   Reconstruction of shield tunnel lining using point cloud [J].
Duan, Dong-Ya ;
Qiu, Wen-Ge ;
Cheng, Yun-Jian ;
Zheng, Yu-Chao ;
Lu, Feng .
AUTOMATION IN CONSTRUCTION, 2021, 130
[10]   Effective Scanning Range Estimation for Using TLS in Construction Projects [J].
Huang, Hong ;
Zhang, Cheng ;
Hammad, Amin .
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2021, 147 (09)