Machine vision techniques are used for speeding up evaluation process, saving evaluation cost, and alleviating the challenge of not having structural specialists available in a local area.
Manual visual inspection is required to determine the condition of damaged buildings after a disaster, such as an earthquake. The lack of available inspectors, when combined with the large volume of inspection work needed after a disaster makes such inspection subjective and time-consuming. Completing the required inspection can take months to complete, which has adverse economic and societal impacts on the affected population.
Doctoral students Zhenhua Zhu, Sara Roberts, Master student Stephanie German, and a CEE Assistant Professor Ioannis Brilakis, and Professor Reginald DesRoches, with support from the U.S. National Science Foundation (Grant # 1000700), are validating the ability of a novel framework for rapid post-earthquake building evaluation that promises to reduce the time needed to evaluate a structure. Under the framework, the visible damage inflicted on critical structural members (concrete columns in this study) is first detected with a novel method of the authors. The spatial properties of the detected damage (cracks, spalling and bucking in this study) are then measured in relation to the column’s dimensions and orientation, so that the column’s load bearing capacity can be approximated as a damage index. The column damage index supplemented with other building information (e.g. structural type and columns arrangement) is then used to query fragility curves of similar buildings, constructed from the analyses of existing and on-going experimental data. The query estimates the probability of the building being in different damage states. The framework is expected to automate the collection of building damage data, to provide a quantitative assessment of the building damage state, and to estimate the vulnerability of the building to collapse in the event of an aftershock. Videos and manual assessments of structures after the 2009 earthquake in Haiti are used to test the framework.