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

Xiangyang Xu, Hao Yang and Boris Kargoll

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 11, 1550147719884886

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: Terrestrial laser scanning; B-spline approximation; robust modeling; rank-based estimator; health monitoring (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:11:p:1550147719884886

DOI: 10.1177/1550147719884886

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