Details
| Original language | English |
|---|---|
| Journal | Advances in mechanical engineering |
| Volume | 10 |
| Issue number | 5 |
| Early online date | 4 May 2018 |
| Publication status | Published - May 2018 |
Abstract
With the development of subways and tunnels, health monitoring of these structures are more and more important. Terrestrial laser scanning is an essential highly accurate technology used to obtain the point clouds data. However, the enormous quantity of point cloud of a tunnel makes it difficult to monitor the long-distance tunnel effectively and efficiently. Therefore, a fast and accurate extraction method is critical for the health monitoring of tunnel structures. In this article, a “Circular Likelihood” method is investigated. The innovation of this study is the consideration of the symmetry and the circular shape of the tunnel structure, where most of the noise can be removed and lots of inefficient iterations are avoided; thus, the computing time is greatly shortened.
Keywords
- circular filtering, data extraction, point cloud, terrestrial laser scanning, Tunnel structures
ASJC Scopus subject areas
- Engineering(all)
- Mechanical Engineering
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In: Advances in mechanical engineering, Vol. 10, No. 5, 05.2018.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Time-efficient filtering method for three-dimensional point clouds data of tunnel structures
AU - Xu, Xiangyang
AU - Yang, Hao
AU - Neumann, Ingo
N1 - Funding Information: 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 Leibniz Universität 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 Hanover for their valid information and help.
PY - 2018/5
Y1 - 2018/5
N2 - With the development of subways and tunnels, health monitoring of these structures are more and more important. Terrestrial laser scanning is an essential highly accurate technology used to obtain the point clouds data. However, the enormous quantity of point cloud of a tunnel makes it difficult to monitor the long-distance tunnel effectively and efficiently. Therefore, a fast and accurate extraction method is critical for the health monitoring of tunnel structures. In this article, a “Circular Likelihood” method is investigated. The innovation of this study is the consideration of the symmetry and the circular shape of the tunnel structure, where most of the noise can be removed and lots of inefficient iterations are avoided; thus, the computing time is greatly shortened.
AB - With the development of subways and tunnels, health monitoring of these structures are more and more important. Terrestrial laser scanning is an essential highly accurate technology used to obtain the point clouds data. However, the enormous quantity of point cloud of a tunnel makes it difficult to monitor the long-distance tunnel effectively and efficiently. Therefore, a fast and accurate extraction method is critical for the health monitoring of tunnel structures. In this article, a “Circular Likelihood” method is investigated. The innovation of this study is the consideration of the symmetry and the circular shape of the tunnel structure, where most of the noise can be removed and lots of inefficient iterations are avoided; thus, the computing time is greatly shortened.
KW - circular filtering
KW - data extraction
KW - point cloud
KW - terrestrial laser scanning
KW - Tunnel structures
UR - http://www.scopus.com/inward/record.url?scp=85048028542&partnerID=8YFLogxK
U2 - 10.1177/1687814018773159
DO - 10.1177/1687814018773159
M3 - Article
AN - SCOPUS:85048028542
VL - 10
JO - Advances in mechanical engineering
JF - Advances in mechanical engineering
SN - 1687-8132
IS - 5
ER -