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 (3σ) 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.

中文翻译：

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基于 LiDAR 检测的盾构隧道管片节理识别与自动分割

本研究提出了一种使用光检测和测距 （LiDAR） 识别接头和自动分割盾构隧道的新方法。在圆柱坐标中，Hough 变换用于提取与不同方位角的环形接头相对应的特征 LiDAR 数据。这种使用 LiDAR 数据的特征提取有助于计算环形关节特征坐标和平均环形关节宽度。随后，使用 M−estimator 样本共识 （MSAC） 算法拟合包含环形接头的平面，从而成功识别和分割隧道 LiDAR 数据中的环形接头。将 LiDAR 数据分割成不同的环形 LiDAR 数据后，使用三西格玛 （3σ） 准则提取纵向关节端点的坐标。然后确定纵向接头的平均宽度。在难以提取纵向连接点的情况下，利用设计模型中的方位角差异来计算方位角。这种方法可以在 LiDAR 数据中进行联合识别，也可以对各个部分进行几何分割。所提出的方法通过洛阳地铁 2 号线的案例研究进行了验证。结果表明，该分割方法可以准确提取大部分环状和纵向节理。此外，这些结果不仅可用于监测结构健康状况，还可用于为隧道开发建筑信息模型 （BIM）。