Sensitivity analysis of augmented reality-assisted building damage reconnaissance using virtual prototyping

The timely and accurate assessment of the damage sustained by a building during catastrophic events, such as earthquakes or blasts, is critical in determining the building's structural safety and suitability for future occupancy. Among many indicators proposed for measuring structural integrity, especially inelastic deformations, Interstory Drift Ratio (IDR) remains the most trustworthy and robust metric at the story level. In order to calculate IDR, researchers have proposed several nondestructive measurement methods. Most of these methods rely on pre-installed target panels with known geometric shapes or with an emitting light source. Such target panels are difficult to install and maintain over the lifetime of a building. Thus, while such methods are nondestructive, they are not entirely non-contact. This paper proposes an Augmented Reality (AR)-assisted non-contact method for estimating IDR that does not require any pre-installed physical infrastructure on a building. The method identifies corner locations in a damaged building by detecting the intersections between horizontal building baselines and vertical building edges. The horizontal baselines are superimposed on the real structure using an AR algorithm, and the building edges are detected via a Line Segment Detection (LSD) approach. The proposed method is evaluated using a Virtual Prototyping (VP) environment that allows testing of the proposed method in a reconfigurable setting. A sensitivity analysis is also conducted to evaluate the effect of instrumentation errors on the method's practical use. The experimental results demonstrate the potential of the new method to facilitate rapid building damage reconnaissance, and highlight the instrument precision requirements necessary for practical field implementation.