Quantification and Evaluation of Roughness of Initial Support Using Terrestrial Laser Scanning

The control of initial support roughness is crucial to the structural waterproofing, durability, and safety of the drilling and blasting tunnel. The existing manual-based measurement methods and evaluation systems have many shortcomings in terms of efficiency, coverage, accuracy, and reliability, which make it difficult to achieve comprehensive measurement, precise quantification, and reliable evaluation of the initial support roughness. In view of this, this paper proposes a method for measuring the deviation of the initial support surface based on terrestrial laser scanning (TLS) technology, which achieves the automated measurement of the longitudinal and circumferential roughness characteristics of the initial support. Through the comparison experiment, it is demonstrated that the deviation measurement method proposed in the paper shows high accuracy, with an average error of 5.4 mm, which is much better than the current criteria and meets the measurement accuracy requirement of tunnel projects. On this basis, we propose a system for quantifying and evaluating the initial support roughness. This paper proposes indicators such as the root-mean square of the deviation (Drms), the skewness of the deviation (Dsk), and the kurtosis of the deviation (Dku) to quantify the roughness from three dimensions, such as the amplitude of the deviation, the degree of surface inclination, and the sharpness of the wave peaks, respectively, which significantly improves the accuracy, comprehensiveness, and richness of the roughness evaluation. Finally, a three-dimensional model of the initial support surface with a color-coded map was used to visualize the multidimensional roughness of the different inspection areas and to accurately locate areas of poor roughness level in the construction coordinate system. The aforementioned work is of great help in identifying, evaluating, locating, and treating initial support surface distresses.

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Publication Details

Journal
Journal of Computing in Civil Engineering
Published
2024-10-28
DOI
https://doi.org/10.1061/jccee5.cpeng-6069
Citations
16
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
Field-Weighted Citation Impact
4.17
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article

Quantification and Evaluation of Roughness of Initial Support Using Terrestrial Laser Scanning

Qasim Zaheer, Xianhua Liu, Jin Wang, Weidong Wang et al.
16 citations
Journal of Computing in Civil Engineering
Infrastructure Maintenance and Monitoring
4.17
article

Quantification and Evaluation of Roughness of Initial Support Using Terrestrial Laser Scanning

Qasim Zaheer, Xianhua Liu, Jin Wang, Weidong Wang, Shi Qiu, Xiao Wei, Jijun Wang, Chunzhong Xiao
article en
16 citations

Abstract

The control of initial support roughness is crucial to the structural waterproofing, durability, and safety of the drilling and blasting tunnel. The existing manual-based measurement methods and evaluation systems have many shortcomings in terms of efficiency, coverage, accuracy, and reliability, which make it difficult to achieve comprehensive measurement, precise quantification, and reliable evaluation of the initial support roughness. In view of this, this paper proposes a method for measuring the deviation of the initial support surface based on terrestrial laser scanning (TLS) technology, which achieves the automated measurement of the longitudinal and circumferential roughness characteristics of the initial support. Through the comparison experiment, it is demonstrated that the deviation measurement method proposed in the paper shows high accuracy, with an average error of 5.4 mm, which is much better than the current criteria and meets the measurement accuracy requirement of tunnel projects. On this basis, we propose a system for quantifying and evaluating the initial support roughness. This paper proposes indicators such as the root-mean square of the deviation (Drms), the skewness of the deviation (Dsk), and the kurtosis of the deviation (Dku) to quantify the roughness from three dimensions, such as the amplitude of the deviation, the degree of surface inclination, and the sharpness of the wave peaks, respectively, which significantly improves the accuracy, comprehensiveness, and richness of the roughness evaluation. Finally, a three-dimensional model of the initial support surface with a color-coded map was used to visualize the multidimensional roughness of the different inspection areas and to accurately locate areas of poor roughness level in the construction coordinate system. The aforementioned work is of great help in identifying, evaluating, locating, and treating initial support surface distresses.

Journal of Computing in Civil EngineeringVol. 39(1)
Central South University (CN), China Academy of Railway Sciences (CN)
Openalex Percentile: Top 5%
Infrastructure Maintenance and Monitoring
4.17
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