An approach to automated detection of structural failure using chronological image analysis in temporary structures

This study explores new technologies for detecting structural failures in temporary structures by applying image processing techniques for the automated detection of structural failures. Temporary structures provide support for permanent structures during construction and serve as work platforms for construction workers, but most standards for temporary structures are voluntary. Design and construction considerations, therefore, are thus left to individual engineering judgement. The new approach utilizes a series of chronological digital images to detect incipient structural instability during the construction process. Any structural deformation becomes a measurable variable through image analysis and can serve as a measurable harbinger of structural failure. The proposed technology matches images in the series with their predecessors to highlight and locate differences in the structure. The small-scale experiment conducted and validated that the proposed methodology shows great potential for detecting micro changes that are too small to be detected by eye. The chronological images are expected to provide a coherent and persistent structural deficiency data-set that can be applied to diagnose physical forms of failure at an early stage of deformation, defining a clear starting point for rehabilitation and enabling structural engineers to draft and implement a comprehensive plan to address incipient problems in temporary structures.