Intelligent monitoring and residual analysis of tunnel point cloud data based on free-form approximation

Xu, Xiangyang; Wang, Zihan; Shi, Peixin; Liu, Wei; Tang, Qiang; Bao, Xiaohua; Chen, Xiang-Sheng; Yang, Hao

doi:10.1080/15376494.2022.2041775

Cited by 10 publications

(3 citation statements)

References 30 publications

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“…We found that the B-spline curves performed best in terms of accuracy, robustness, and rate for n = 3 and p = 10. The specific research process is described in [33]. Therefore, n = 3 and p = 10 was selected as the B-spline parameters for this entire process.…”

Section: B-spline Parameter Selectionmentioning

confidence: 99%

Automatic Identification and Intelligent Optimization of Tunnel-Free Curve Reconfiguration

Wang

Shi

et al. 2022

Symmetry

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Extracting complete cross-sectional geometric features from the large amount of point cloud data acquired by laser scanners plays an important part in the detection of deformations in tunnel inspection projects. Tunnel cross-sections have symmetrical geometric features, and information is traditionally collected manually. The traditional manual extraction of point clouds is inefficient and limited by the subjectivity of the operators when addressing the problems. This paper proposes a new algorithm for the automatic identification of tunnel lining section curves, the rapid separation of common interference targets, and the optimization of curve geometry features. The innovation of this approach lies in the combination of B-spline and Euclidean clustering methods and the comprehensive evaluation of the denoising results in terms of precision, recall, F-score, and rand index (RI). In this way, the automatically extracted health point cloud data are refitted to optimize the tunnel profile model.

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Section: B-spline Parameter Selectionmentioning

confidence: 99%

Automatic Identification and Intelligent Optimization of Tunnel-Free Curve Reconfiguration

Wang

Shi

et al. 2022

Symmetry

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“…The goal is to minimize the adverse effects of visible light cameras' sensitivity to light. Xu et al [6] employed a residual classification technique to intelligently detect common interference targets. They also presented an approach for intelligently monitoring and analyzing residual tunnel point cloud data using free-form approximation.…”

Section: Introductionmentioning

confidence: 99%

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features

Qiu,

Zhu,

Wang

et al. 2024

Meas. Sci. Technol.

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The multi vision metro tunnel defect sensing system mainly consists of IRT and RGB cameras, which can automatically identify and extract small tunnel lining surface defects, greatly improving detection efficiency. However, the presence of various issues like train vibration, inconsistent lighting, fluctuations in temperature and humidity leads to the images showing inadequate uniformity in illumination, blurriness, and a decrease in the level of detail. The above issues have led to unsatisfactory fusion processing results for multiple visual images and increased missed detection rates. A multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features is proposed. This method first takes the motion state of the train and the blurry image as constraints to eliminate dynamic blurring in the image. Secondly, Image weights are allocated based on the uniformity of visible light image illumination in the tunnel, as well as real-time temperature and humidity. Finally, image feature extraction and fusion are performed by a U-Net network that integrates channel attention mechanisms. The experimental results demonstrate that this approach improves the image pixel value variation rate by 39.7%, enhances the edge quality by 23%, and outperforms similar approach in terms of average gradient, gradient quality, and sum of difference correlation with improvements of 15.9%, 7.3%, and 26.6% respectively.

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“…A finite element model is established based on the soft soil layers and segment patterns of Shanghai Metro Line 5, and the applicability of the model is verified by calculating deformations using three-dimensional laser scanning point clouds of sections from Shanghai Metro Line 5. The method for processing point clouds is based on the author's previous research [27][28][29]. Suitable subgrade reaction coefficients and lateral pressure coefficients are determined by adjusting the bending stiffness of the beam-spring model's connection springs for ring segment joints.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation Study Considering Discontinuous Longitudinal Joints in Soft Soil under Symmetric Loading

He,

Xu,

Yang

2024

Symmetry

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In shield tunneling, the joint is one of the most vulnerable parts of the segmental lining. Opening of the joint reduces the overall stiffness of the ring, leading to structural damage and issues such as water leakage. Currently, the Winkler method is commonly used to calculate structural deformation, simplifying the interaction between segments and soil as radial and tangential Winkler springs. However, when introducing connection springs or reduction factors to simulate the joint stiffness of segments, the challenge lies in determining the reduction coefficient and the stiffness of the springs. Currently, the hyperstatic reflection method cannot simulate the discontinuity effect at the connection of the tunnel segments, while the state space method overlooks the nonlinear interaction between the tunnel and the soil. Therefore, this paper proposes a numerical simulation method considering the interaction between the tunnel and the soil, which is subjected to compression rather than tension, and the discontinuity of the joints between the segments. The model structure and external load are symmetrical, resulting in symmetrical calculation results. This method is based on the soft soil layers and shield tunnel structures of the Shanghai Metro, and the applicability of the model is verified through deformation calculations using three-dimensional laser scanning point clouds of sections from the Shanghai Metro Line 5. When the subgrade reaction coefficient is 5000 kN/m3, the model can effectively simulate the deformation of operational tunnels. By adjusting the bending stiffness of individual connection springs, we investigate the influence of bending stiffness reduction on the bending moment, radial displacement, and rotational displacement of the ring. The results indicate that a decrease in joint bending stiffness significantly affects the mechanical response of the ring, and the extent and degree of this influence are correlated with the joint position and the magnitude of joint bending stiffness.

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Intelligent monitoring and residual analysis of tunnel point cloud data based on free-form approximation

Cited by 10 publications

References 30 publications

Automatic Identification and Intelligent Optimization of Tunnel-Free Curve Reconfiguration

Automatic Identification and Intelligent Optimization of Tunnel-Free Curve Reconfiguration

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features

Numerical Simulation Study Considering Discontinuous Longitudinal Joints in Soft Soil under Symmetric Loading

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