Hierarchical Inspection System Using Visual and MFL Probe Robots

Uvais Qidwai, Muhammad Akbar, Muhammad Maqbool, Mohammed Jahanshahi

Abstract


Structural Health Monitoring (SHM) represents a critical appurtenance to modern engineering that amalgamates the skills and techniques from various disciplines of engineering and computational science. Modern civil architectures, involving high-rise buildings, complex structural designs, and innovative shapes, on one hand represent the urban development, but at the same time is a challenge from sustainability perspective. In order to ensure the tenability of such structures, advanced SHM procedures need to be developed. The presented work in this paper is an effort on these lines. The wear and tear in the buildings related to weather, as well as other natural disasters, needs to be monitored regularly and systematically in order to prevent any serious structural damage. In current SHM practices, human experts are deployed at various structurally critical places on these buildings to perform specific measurements and analyze them to decide on the structural health condition. This simple approach is becoming more and more complicated as well as perilous for the human personnel involved, due to the modern architecture that involves greater heights, and complex structures. The proposed system utilizes flying and crawling/roving robots for this purpose. The flying robots, first, scan the surface of the building to any height needed, and then the custom-designed algorithms analyze the images from these scans in order to discern the possible defects/anomalies in the structure. Using these defect pointers, the custom-designed rover robot on top of the structure lowers a robotic probe that scans only those areas for substantiating the anomalies and the degree of defects present.


Keywords


Computer vision, Magnetic flux leakage (MFL) Progressive image stitching, Structural inspection, Unmanned-aerial vehicle (UAV),

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DOI: http://doi.org/10.11591/ijra.v7i4.pp283-296
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.