Abstract
Abstract. The quality of tunnel excavation is evaluated by comparing the excavated tunnel and the design model. Terrestrial laser scanning (TLS) provides surveyors with dense and accurate three-dimensional (3D) point clouds for excavation model reconstruction. However, sufficient attention has not been paid to incorporating design models for tunnel point cloud processing. In this paper, a technical framework that combines TLS point clouds and the design model for tunnel excavation evaluation is proposed. Firstly, the point clouds are sliced into cross-sections and the feature points are accordingly extracted. Then, considering the structure of the design model, feature point deficiencies are repaired by topological and parametric model interpolation. Finally, the excavation quality is evaluated in terms of the deviation of centerlines and 3D models. This method is validated in the case study. Experiments show that the deviation of centerline azimuth is acceptable but there remain considerable overbreak and underbreak, which respectively account for 20.6% and 11.2% of the design excavation volume.
Highlights
As important infrastructures of water conservancy and transportation engineering, a considerable number of tunnels have been excavated in recent years
Incorporating the design model, the excavation quality is evaluated in terms of centerlines and 3D models
The curvature radius of the design model of segment BC is 150.00 m and the extracted curvature radius is 149.951 m. These results reveal that the bias between the excavation centerline and the design centerline is acceptable for constructors
Summary
As important infrastructures of water conservancy and transportation engineering, a considerable number of tunnels have been excavated in recent years. During the excavation by drilling or blasting, constructors have to evaluate the deviation between the excavated tunnel and the design model, including the volume of underbreak or overbreak and the bias of centerlines (Cui et al, 2019; Fekete et al, 2010). These indicators reflect the quality of excavation and guide the subsequent project arrangement (Xu et al, 2018). Case studies demonstrated that creating a 3D polygon mesh model was demanding in terms of computational resources, and led to geometry ambiguity in the form of overlapping faces (Gikas, 2012)
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