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Building Earthquake Damage Analysis Using Terrestrial Laser Scanning Data

Author(s):


Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2019
Page(s): 1-12
DOI: 10.1155/2019/8308104
Abstract:

Terrestrial laser scanners (TLSs) can acquire high-precision three-dimensional point cloud data for earthquake-damaged buildings. In this study, we collected TLS data in the Wenchuan earthquake zone and developed the TLS-BSAM (terrestrial laser scanning-based building shape analysis model) to carry out a building earthquake damage analysis. This model involves equidistance polygon array extraction, shape dispersion parameter calculations, irregular building clustering segmentation, and damage analysis. We chose 21 buildings as samples for the experiments. The results show that when using an equidistance polygon array to depict a three-dimensional building, 0.5 m is a reasonable sampling interval for building earthquake damage analysis. Using certain characteristic parameters to carry outK-means clustering, one can efficiently divide irregular buildings into regular blocks. Then, by weighted averages, the shape dispersion parameters can be calculated to express the damage extent to buildings. Among the shape dispersion parameters, at least the weighted average standard deviations of the tilt direction, rectangularity, compactness, and center point are suitable to reflect the damage extent. Higher values reflect more serious damage. On the basis of existing data, the weighted average standard deviations of the tilt direction and center point can be used to establish discriminant functions that can effectively distinguish the damage extent.

Copyright: © 2019 Qisong Jiao et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10314298
  • Published on:
    07/06/2019
  • Last updated on:
    02/06/2021
 
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