3D point cloud registration is a crucial technique for point cloud processing. Iterative closest point (ICP) is widely used for rigid registration of point clouds because of its simplicity but suffers from slow convergence and the tendency to fall into local optimization. In this paper, we proposed a new robust and fast point cloud registration method, the ICP optimized by geometric features (including normal, curvature, and point distance), called GFOICP. GFOICP statistically selects registration points by the cross-entropy of geometric features of the points, then matches correspondences based on a variable distance threshold and filters out correct correspondences using an iterative strict constraint on geometric feature similarity. In addition, geometric feature similarity is added as a constraint to the objective function to ensure strict convergence. GFOICP completes registration by iterating correspondence matching, alignment, and convergence judgment. Extensive experiments on publicly available synthetic and real-world datasets have demonstrated that GFOICP significantly improves accuracy and speed compared to standard ICP. GFOICP has similar or higher accuracy and speed than other state-of-the-art registration methods.

Given the flammability of power cables and the high cost of utility tunnel construction, power cable fires cause serious economic losses and are associated with a negative social impact. In the study, a weighted fuzzy Petri net and an event tree are combined to propose a quantitative evaluation method to mitigate cable fire risks in a utility tunnel. First, cable fire risk factors are analyzed. Given the lack of utility tunnel cable fire historical data, fuzzy theory is used to calculate the failure probability of the primary event. Second, a weighted fuzzy Petri net is used for fuzzy reasoning, and an event tree is used to analyze all possible consequences. Subsequently, the numerical simulation method is used to quantify the loss from the cable fire and thereby quantify the risk of cable fire. Finally, the effect of different risk factors on a cable fire is analyzed to determine the main factors that affect cable fires. Simultaneously, the control ability of different control measures with respect to the fire is analyzed to determine key control measures. A case study of a utility tunnel cable cabin in Liupanshui in Guizhou is employed to validate the utility of the proposed method.

This paper studies the limitations of binocular vision technology in monitoring accuracy. The factors affecting the surface displacement monitoring of the slope are analyzed mainly from system structure parameters and environment parameters. Based on the error analysis theory, the functional relationship between the structure parameters and the monitoring error is studied. The error distribution curve is obtained through laboratory testing and sensitivity analysis, and parameter selection criteria are proposed. Corresponding image optimization methods are designed according to the error distribution curve of the environment parameters, and a large number of tests proved that the methods effectively improved the measurement accuracy of slope deformation monitoring. Finally, the reliability and accuracy of the proposed system and method are verified by displacement measurement of a slope on site.

The paper presents an intelligent real-time slope surface deformation monitoring system based on binocular stereo-vision. To adapt the system to field slope monitoring, a design scheme of concentric marking point is proposed. Techniques including Zernike moment edge extraction, the least squares method, and k-means clustering are used to design a sub-pixel precision localization method for marker images. This study is mostly focused on the tracking accuracy of objects in multi-frame images obtained from a binocular camera. For this purpose, the Upsampled Cross Correlation (UCC) sub-pixel template matching technique is employed to improve the spatial-temporal contextual (STC) target-tracking algorithm. As a result, the tracking accuracy is improved to the sub-pixel level while keeping the STC tracking algorithm at high speed. The performance of the proposed vision monitoring system has been well verified through laboratory tests.

With the large‐scale construction of urban rail transit, it will lead to the intersection and transfer of various lines, resulting in more transfer stations. The transfer station is a collection point for multiple subway lines, which is difficult to construct and has a high construction risk. The construction of the new subway station and the operation of the existing subway station are mutually influenced during the close‐attached undercrossing construction. Considering the two objectives of ensuring the smooth operation of the existing subway station and the safe construction of the new subway station, this paper comprehensively analyzes the possible safety risk factors during the construction of the new subway station close‐attached undercrossing the existing operating station and identifies 75 preliminary risk factors by means of literature review and on‐site investigation. Then the Delphi Method and Entropy Weight Method are used to screen the preliminary risk factors, and the main risk factors with greater influence are retained, so that 49 key risk factors are obtained. According to the list of key risk factors, a safety risk assessment index system including 2 first‐level indexes, 12 second‐level indexes, and 49 third‐level indexes is established. Based on the index system, this paper establishes a safety risk assessment model by using Analytic Hierarchy Process (AHP) and Fuzzy Matter Element Method (FMEM). The model first calculates the weight of each index by using AHP, calculates the comprehensive correlation degree of each index by using FMEM, classifies the risk grade of each index according to the comprehensive correlation degree, and determines the risk grade of the project. Finally, the safety risk assessment model is applied to the Dongdalu Station project of Chengdu Rail Transit Line 8. The result shows that the risk grade of this project is moderate risk, which is basically consistent with the actual situation, indicating that the model has good practicability. In this paper, a new safety risk assessment model for subway close‐attached undercrossing construction is proposed, which fills the gap in the field of safety risk assessment for the construction of the new subway station close‐attached undercrossing the existing operating station.