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

verfasst von
Xiangyang Xu, Hao Yang, Boris Kargoll
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.

Organisationseinheit(en)
Geodätisches Institut
Externe Organisation(en)
Jiangsu University of Science and Technology (JUST)
Typ
Artikel
Journal
International Journal of Distributed Sensor Networks
Band
15
ISSN
1550-1329
Publikationsdatum
11.2019
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Ingenieurwesen (insg.), Computernetzwerke und -kommunikation
Elektronische Version(en)
https://doi.org/10.1177/1550147719884886 (Zugang: Offen)
https://doi.org/10.15488/10180 (Zugang: Offen)
 

Details im Forschungsportal „Research@Leibniz University“