Next Article in Journal
Regional Recognition and Classification of Active Loess Landslides Using Two-Dimensional Deformation Derived from Sentinel-1 Interferometric Radar Data
Next Article in Special Issue
Historical Underground Structures as 3D Cadastral Objects
Previous Article in Journal
An Efficient Processing Approach for Colored Point Cloud-Based High-Throughput Seedling Phenotyping
Previous Article in Special Issue
New Heights of the Highest Peaks of Polish Mountain Ranges
 
 
Article

3D Point Cloud Analysis for Damage Detection on Hyperboloid Cooling Tower Shells

Department of Land Surveying, Faculty of Environmental Engineering and Land Surveying, University of Agriculture in Kraków, 30-059 Kraków, Poland
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(10), 1542; https://doi.org/10.3390/rs12101542
Received: 28 February 2020 / Revised: 17 April 2020 / Accepted: 11 May 2020 / Published: 12 May 2020
The safe operation and maintenance of the appropriate strength of hyperboloid cooling towers require special supervision and a maintenance plan that takes into consideration the condition of the structure. With three series of terrestrial laser scanning data, the paper presents an automatic inspection system for reinforced concrete cooling tower shells that ensures detection and measurement of damage together with the verification of the quality and durability of surface repairs as required by industry standards. The proposed solution provides an automatic sequence of algorithm steps with low computational requirements. The novel method is based on the analysis of values of the local surface curvature determined for each point in the cloud using principal component analysis and transformed using the square root function. Data segmentation into cloud points representing a uniform shell and identified defects was carried out using the region growing algorithm. The extent of extracted defects was defined through vectorisation with a convex hull. The proposed diagnostics strategy of reinforced concrete hyperboloid cooling towers was drafted and validated using an object currently under repair but in continuous service for fifty years. The results of detection and measurement of defects and verification of surface continuity at repaired sites were compared with traditional diagnostics results. It was shown that the sequence of algorithm steps successfully identified all cavities, scaling, and blisters in the shell recorded in the expert report (recognition rate—100%). Cartometric vectorisation of defects determined the scope of necessary shell repairs offering higher performance and detail level than direct contact measurement from suspended platforms. Analysis of local geometric features of repaired surfaces provided a reliable baseline for the evaluation of the repairs aimed at restoring the protective properties of the concrete surround, desirable especially in the warranty period. View Full-Text
Keywords: terrestrial laser scanning (TLS); non-destructive testing (NDT); laser-based defect detection; surface damage quantification; automated construction monitoring; analysis of reinforced concrete structure; 3D technology measurement; curvature estimation; principal component analysis (PCA) terrestrial laser scanning (TLS); non-destructive testing (NDT); laser-based defect detection; surface damage quantification; automated construction monitoring; analysis of reinforced concrete structure; 3D technology measurement; curvature estimation; principal component analysis (PCA)
Show Figures

Figure 1

MDPI and ACS Style

Makuch, M.; Gawronek, P. 3D Point Cloud Analysis for Damage Detection on Hyperboloid Cooling Tower Shells. Remote Sens. 2020, 12, 1542. https://doi.org/10.3390/rs12101542

AMA Style

Makuch M, Gawronek P. 3D Point Cloud Analysis for Damage Detection on Hyperboloid Cooling Tower Shells. Remote Sensing. 2020; 12(10):1542. https://doi.org/10.3390/rs12101542

Chicago/Turabian Style

Makuch, Maria, and Pelagia Gawronek. 2020. "3D Point Cloud Analysis for Damage Detection on Hyperboloid Cooling Tower Shells" Remote Sensing 12, no. 10: 1542. https://doi.org/10.3390/rs12101542

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop