Condition diagnostics of steel water tanks using correlated visual patterns Kalasapudi, Vamsi Sai; Tang, Pingbo
Insufficient, unreliable, and delayed condition assessment of steel water tanks is causing poor maintenance planning, wastes of maintenance resources, and unexpected structure failures. Visual inspection of water tanks heavily relies on engineers’ experiences for achieving comprehensive and reliable condition assessments. Recent studies reveal the potential of using imaging technology for improving the efficiency and comprehensiveness of capturing visual conditions of large civil infrastructures, but manual interpretation of imagery data still impedes engineers from reliable awareness of structural conditions. On the other hand, some studies show that deteriorations of structures result in correlated visual patterns that can assist engineers in structural diagnosis. The objective of the research presented in this paper is to examine correlated deformation patterns of a steel tank based on analyzing 3D laser-scanned point clouds collected in the field. Specifically, the authors aim at identifying correlated shape change patterns of a water tank through various 3D data analysis algorithms, and synthesize these 3D data patterns as knowledge for guiding data-driven condition assessment of the water tank. The authors examined two 3D data analysis approaches for revealing the deformation patterns of the studied tank. The first approach calculates the deviations of the 3D data points from as-designed shapes of the water tank for identifying structural deformation and defects. The second approach visualized anomalous variations in local shape descriptors, such as curvature, for identifying defects of structures. Correlations between the patterns could then reveal systematic changes of the tank for helping engineers conduct more reliable condition assessments.
Item Citations and Data
Attribution-NonCommercial-NoDerivs 2.5 Canada