Robust and automatic modeling of tunnel structures based on terrestrial laser scanning measurement

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Xiangyang Xu
  • Hao Yang
  • Boris Kargoll

Research Organisations

External Research Organisations

  • Jiangsu University of Science and Technology
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Details

Original languageEnglish
JournalInternational Journal of Distributed Sensor Networks
Volume15
Issue number11
Early online date4 Nov 2019
Publication statusPublished - Nov 2019

Abstract

The terrestrial laser scanning technology is increasingly applied in the deformation monitoring of tunnel structures. However, outliers and data gaps in the terrestrial laser scanning point cloud data have a deteriorating effect on the model reconstruction. A traditional remedy is to delete the outliers in advance of the approximation, which could be time- and labor-consuming for large-scale structures. This research focuses on an outlier-resistant and intelligent method for B-spline approximation with a rank (R)-based estimator, and applies to tunnel measurements. The control points of the B-spline model are estimated specifically by means of the R-estimator based on Wilcoxon scores. A comparative study is carried out on rank-based and ordinary least squares methods, where the Hausdorff distance is adopted to analyze quantitatively for the different settings of control point number of B-spline approximation. It is concluded that the proposed method for tunnel profile modeling is robust against outliers and data gaps, computationally convenient, and it does not need to determine extra tuning constants.

Keywords

    B-spline approximation, health monitoring, rank-based estimator, robust modeling, Terrestrial laser scanning

ASJC Scopus subject areas

Cite this

Robust and automatic modeling of tunnel structures based on terrestrial laser scanning measurement. / Xu, Xiangyang; Yang, Hao; Kargoll, Boris.
In: International Journal of Distributed Sensor Networks, Vol. 15, No. 11, 11.2019.

Research output: Contribution to journalArticleResearchpeer review

Xu X, Yang H, Kargoll B. Robust and automatic modeling of tunnel structures based on terrestrial laser scanning measurement. International Journal of Distributed Sensor Networks. 2019 Nov;15(11). Epub 2019 Nov 4. doi: 10.1177/1550147719884886, 10.15488/10180
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abstract = "The terrestrial laser scanning technology is increasingly applied in the deformation monitoring of tunnel structures. However, outliers and data gaps in the terrestrial laser scanning point cloud data have a deteriorating effect on the model reconstruction. A traditional remedy is to delete the outliers in advance of the approximation, which could be time- and labor-consuming for large-scale structures. This research focuses on an outlier-resistant and intelligent method for B-spline approximation with a rank (R)-based estimator, and applies to tunnel measurements. The control points of the B-spline model are estimated specifically by means of the R-estimator based on Wilcoxon scores. A comparative study is carried out on rank-based and ordinary least squares methods, where the Hausdorff distance is adopted to analyze quantitatively for the different settings of control point number of B-spline approximation. It is concluded that the proposed method for tunnel profile modeling is robust against outliers and data gaps, computationally convenient, and it does not need to determine extra tuning constants.",
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N1 - Funding information: The authors would like to acknowledge the support of Natural Science Foundation of Jiangsu Province (No. BK20160558). The authors also wish to acknowledge the support of all the colleagues in Geodetic Institute of Leibniz University Hannover. The authors would like to acknowledge the support of Natural Science Foundation of Jiangsu Province (No. BK20160558). The authors also wish to acknowledge the support of all the colleagues in Geodetic Institute of Leibniz University Hannover. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The publication of this article was funded by the Open Access Fund of the Leibniz Universit?t Hannover. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The publication of this article was funded by the Open Access Fund of the Leibniz Universität Hannover.

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