TY - JOUR

T1 - Intelligent crack extraction and analysis for tunnel structures with terrestrial laser scanning measurement

AU - Xu, Xiangyang

AU - Yang, Hao

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 the Leibniz Universität Hannover. The authors gratefully acknowledge the support of the Natural Science Foundation of Jiangsu Province (grant no. BK20160558).

PY - 2019/9

Y1 - 2019/9

N2 - An automatic and intelligent method for crack detection is significantly important, considering the popularity of large constructions. How to identify the cracks intelligently from massive point cloud data has become increasingly crucial. Terrestrial laser scanning is a measurement technique for three-dimensional information acquisition which can obtain coordinates and intensity values of the laser reflectivity of a dense point cloud quickly and accurately. In this article, we focus on the optimal parameter of Gaussian filtering to balance the efficiency of crack identification and the accuracy of crack analysis. The innovation of this article is that we propose a novel view of the signal-to-noise ratio gradient for Gaussian filtering to identify and extract the cracks automatically from the point cloud data of the terrestrial laser scanning measurement.

AB - An automatic and intelligent method for crack detection is significantly important, considering the popularity of large constructions. How to identify the cracks intelligently from massive point cloud data has become increasingly crucial. Terrestrial laser scanning is a measurement technique for three-dimensional information acquisition which can obtain coordinates and intensity values of the laser reflectivity of a dense point cloud quickly and accurately. In this article, we focus on the optimal parameter of Gaussian filtering to balance the efficiency of crack identification and the accuracy of crack analysis. The innovation of this article is that we propose a novel view of the signal-to-noise ratio gradient for Gaussian filtering to identify and extract the cracks automatically from the point cloud data of the terrestrial laser scanning measurement.

KW - automatic identification

KW - crack extraction

KW - Intelligent monitoring

KW - terrestrial laser scanning

KW - tunnel structures

UR - http://www.scopus.com/inward/record.url?scp=85073077196&partnerID=8YFLogxK

U2 - 10.1177/1687814019872650

DO - 10.1177/1687814019872650

M3 - Article

AN - SCOPUS:85073077196

VL - 11

JO - Advances in Mechanical Engineering

JF - Advances in Mechanical Engineering

SN - 1687-8132

IS - 9

ER -