3D Point Cloud Analysis for Damage Detection on Hyperboloid Cooling Tower Shells
Maria Makuch , Pelagia Gawronek
AbstractThe 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.
|Journal series||Remote Sensing, ISSN 2072-4292, (N/A 100 pkt)|
|Publication size in sheets||1.1|
|Keywords in English||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)|
|License||Journal (articles only); author's original; ; after publication|
|Publication indicators||: 2017 = 1.559; : 2018 = 4.118 (2) - 2018=4.74 (5)|
|Finansowanie||This research was partly financed by the Ministry of Science and Higher Education of the Republic of Poland (4363/KG/2015, 2307/KG/2018) and is a part of sewed up PhD thesis  of the first Author. APC was funded by the subvention of Minister of Science and Higher Education for the University of Agriculture in Krakow in 2019.|
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