Details
| Original language | English |
|---|---|
| Pages (from-to) | 702-710 |
| Number of pages | 9 |
| Journal | Composite structures |
| Volume | 208 |
| Early online date | 9 Oct 2018 |
| Publication status | Published - 15 Jan 2019 |
Abstract
Automatically modeling and intelligently monitoring composite tunnel structures is of great significance considering the development of composite and diverse tunnel construction materials. Therefore, how to efficiently analyze the deformation of all kinds of tunnel structures with its expanding application is becoming increasingly important. In this paper, we analyze the over- and under-fitting problems under different point cloud profiles to generate an automatic and robust B-spline model which is a suitable method for high accuracy approximation capable of optimizing the composite tunnel model by adjusting the parameters. The innovation of this research is that we combine the maximum likelihood function and the degree of freedom to obtain the optimal parameters model of composite tunnels, which are validated by the various profiles.
Keywords
- B-spline approximation, Likelihood method, Point cloud, Robust estimation, Terrestrial laser scanning, Tunnel structure
ASJC Scopus subject areas
- Materials Science(all)
- Ceramics and Composites
- Engineering(all)
- Civil and Structural Engineering
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In: Composite structures, Vol. 208, 15.01.2019, p. 702-710.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - An automatic and intelligent optimal surface modeling method for composite tunnel structures
AU - Yang, Hao
AU - Xu, Xiangyang
AU - Kargoll, Boris
AU - Neumann, Ingo
N1 - Funding Information: The publication of this article was funded by the Open Access Fund of the Leibniz Universität Hannover. The authors also acknowledge the support of Natural Science Foundation of Jiangsu Province (No: BK20160558 ).
PY - 2019/1/15
Y1 - 2019/1/15
N2 - Automatically modeling and intelligently monitoring composite tunnel structures is of great significance considering the development of composite and diverse tunnel construction materials. Therefore, how to efficiently analyze the deformation of all kinds of tunnel structures with its expanding application is becoming increasingly important. In this paper, we analyze the over- and under-fitting problems under different point cloud profiles to generate an automatic and robust B-spline model which is a suitable method for high accuracy approximation capable of optimizing the composite tunnel model by adjusting the parameters. The innovation of this research is that we combine the maximum likelihood function and the degree of freedom to obtain the optimal parameters model of composite tunnels, which are validated by the various profiles.
AB - Automatically modeling and intelligently monitoring composite tunnel structures is of great significance considering the development of composite and diverse tunnel construction materials. Therefore, how to efficiently analyze the deformation of all kinds of tunnel structures with its expanding application is becoming increasingly important. In this paper, we analyze the over- and under-fitting problems under different point cloud profiles to generate an automatic and robust B-spline model which is a suitable method for high accuracy approximation capable of optimizing the composite tunnel model by adjusting the parameters. The innovation of this research is that we combine the maximum likelihood function and the degree of freedom to obtain the optimal parameters model of composite tunnels, which are validated by the various profiles.
KW - B-spline approximation
KW - Likelihood method
KW - Point cloud
KW - Robust estimation
KW - Terrestrial laser scanning
KW - Tunnel structure
UR - http://www.scopus.com/inward/record.url?scp=85055352891&partnerID=8YFLogxK
U2 - 10.1016/j.compstruct.2018.09.082
DO - 10.1016/j.compstruct.2018.09.082
M3 - Article
AN - SCOPUS:85055352891
VL - 208
SP - 702
EP - 710
JO - Composite structures
JF - Composite structures
SN - 0263-8223
ER -