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In a study published in Minerals, a 3D laser scanning technology-based deformation measurement and monitoring method is proposed for safe and effective tunnel construction. A greedy triangulation and B-spline interpolation were used to fit the tunnel point cloud and characterize the tunnel deformation.

Study: Research on Tunnel Construction Monitoring Method Based on 3D Laser Scanning Technology . Image Credit: Sasa Dzambic Photography/Shutterstock.com

Tunneling is a dangerous but rapidly growing sector in the construction industry. It is regarded as one of the most challenging construction methods due to the presence of debris material, shear zones, water channels, and the unpredictable behavior of the rocks during the construction phase.

An efficient and safe procedure is necessary for saving time while providing a safer workplace for construction.

The new Austrian tunneling method is regarded as the most efficient technique in geologically diverse regions as it employs an analytical approach. However, the new Austrian tunneling method necessitates efficient tunnel monitoring and measurement for estimating tunnel deformation.

Tunnels are symmetrical constructions that must withstand unpredictable loads. Therefore, monitoring and measuring the deformation and stability of the surrounding surface, rock, and supporting structure is crucial to collecting the necessary information for safe tunnel construction.

A total station is often used for monitoring and measurement, with reflective indicators at the measuring stations. However, this method has significant drawbacks, including:

3D laser scanning enables contactless measurements and can directly generate enormous 3D data clouds with irregular spatial distribution. It can also penetrate rocks and is less susceptible to environmental factors.

Due to its strong environmental adaptability, high level of automation, fast detection speed, and good adaptability, 3D laser scanning technology has been increasingly used in tunnel construction. It aids in identifying over and under excavation by comparing the tunnel's design surface to the predicted model by the point and fitted point cloud.

However, 3D laser scanning faces two significant obstacles: abnormal denoising points and random distribution of point clouds.

3D laser scanning obtained distributed clouds of irregular surroundings and structures in the new Austrian tunneling method. The tunnel surfaces were fitted using a greedy triangulation and B-spline interpolation to address the scattered point cloud analysis issue.

The tunnel fitting surface deformation was inventively expressed using the normal vector matrix, which resolved the issue of scattered point clouds in three-dimensional laser scanning.

The maximum entropy method computed the deformation eigenvalues and the normal vector's probability density function. The deformation eigenvalues generated a curve to forecast and assess tunnel deformation.

The values of the greedy triangulation method corresponded well with the fitting surface, demonstrating a better fit than those of the B-spline interpolation method. In addition, the fitted surface's triangles' curvature was reduced as the point cloud density increased.

When the sudden shift in curvature is minor, tunnel displacement and tunnel surface deformation are perpendicular to the tunnel's surface. However, this is only valid if the tunnel is sufficiently flat before monitoring.

By removing the aberrant points brought on by the tunnel surface's lack of flatness, the maximum entropy approach can reliably determine how the tunnel has deformed. However, the maximum entropy method's calculation of the probability density function does not converge when the tunnel deformation and normal vector are small.

Accurate assessment and measurements can be carried out using either the 1% or 5% feature deformation values. However, the exceedance probability is more likely to be disrupted by construction variables when it is too low. The deformation value based on the 5% probability feature may better represent the deformation of each tunnel segment.

In future studies, researchers will implement AI systems to determine the change in the standard vector matrix and the probability density function for estimating the tunnel's deformation trend.

Wei, Z., Wang, Y., Weng, W., Zhou, Z., & Li, Z. (2022) Research on Tunnel Construction Monitoring Method Based on 3D Laser Scanning Technology. Symmetry. https://www.mdpi.com/2073-8994/14/10/2065/htm

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NEBOSH certified Mechanical Engineer with 3 years of experience as a technical writer and editor. Owais is interested in occupational health and safety, computer hardware, industrial and mobile robotics. During his academic career, Owais worked on several research projects regarding mobile robots, notably the Autonomous Fire Fighting Mobile Robot. The designed mobile robot could navigate, detect and extinguish fire autonomously. Arduino Uno was used as the microcontroller to control the flame sensors' input and output of the flame extinguisher. Apart from his professional life, Owais is an avid book reader and a huge computer technology enthusiast and likes to keep himself updated regarding developments in the computer industry.

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