Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.
The indirect displacement estimation using acceleration and strain (IDEAS) method is extended to various types of beam structures beyond the previous validation on the prismatic or near-prismatic beams. By fusing different types of responses, the IDEAS method is able to estimate displacements containing pseudo-static components with high frequency noise to be significantly reduced. However, the concerns to the IDEAS method come from possible disagreement of the assumed sinusoidal mode shapes to the actual mode shapes, which allows the IDEAS method to be valid only for simply-supported prismatic beams and limits its applicability to real world problems. In this paper, the extension of the IDEAS method to the general types of beams is investigated by the mathematical formulation of the modal mapping matrix only for the monitored substructure, so-called monitoring span. The formulation particularly considers continuous and wide beams to extend the IDEAS method to general beam structures that reflect many real bridges. Numerical simulations using four types of beams with various irregularities are presented to show the effectiveness and accuracy of the IDEAS method in estimating displacements.
This paper proposes a static stress estimation method for concrete structures, using the stress relaxation method (SRM) in conjunction with digital image correlation (DIC). The proposed method initially requires a small hole to be drilled in the concrete surface to induce stress relaxation around the hole and, consequently, a displacement field. DIC measures this displacement field by comparing digital images taken before and after the hole-drilling. The stress level in the concrete structure is then determined by solving an optimization problem, designed to minimize the difference between the displacement fields from DIC and the one from a numerical model. Compared to the pointwise measurements by strain gauges, the full-field displacement obtained by DIC provides a larger amount of data, leading to a more accurate estimation. Our theoretical results were experimentally validated using concrete specimens, demonstrating the efficacy of the proposed method.
Stagnant water in asphalt-overlaid bridge decks is a primary cause of deterioration. Rainwater seeping through the asphalt layer stagnates on waterproofing membranes of the bridge deck, consequently degrading the asphalt pavement and the underlying concrete deck. Thus, identifying ponding regions under pavements potentially containing water can facilitate the prognostic maintenance of bridge decks. This study proposes a framework to estimate the subsurface ponding zone in bridge decks using ground-penetrating radar (GPR). The depth distribution of the nonpermeable layer in the subsurface of the bridge is extracted (depth map) from the GPR C-scan using a conventional thickness evaluation method and used to build a bathymetric dendrogram to model subsurface water flows. The subsurface ponding zone can be identified by considering drainage on the bathymetric dendrogram. The proposed framework is demonstrated using an in-service bridge in Korea. The estimated subsurface ponding zone is compared with damage locations of concrete observed after hydrodemolition.
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