• Smart Structures and Systems
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• v.31 no.6
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• pp.573-583
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• 2023

Although unmanned aerial vehicles have been used to overcome the limited accessibility of human-based visual inspection, unresolved issues still remain. Onsite inspectors face difficulty finding previously detected damage locations and tracking their status onsite. For example, an inspector still marks the damage location on a target structure with chalk or drawings while comparing the current status of existing damages to their previous status, as documented onsite. In this study, an augmented-reality-based structural inspection system with onsite damage information marking was developed to enhance the convenience of inspectors. The developed system detects structural damage, creates a holographic marker with damage information on the actual physical damage, and displays the marker onsite via an augmented reality headset. Because inspectors can view a marker with damage information in real time on the display, they can easily identify where the previous damage has occurred and whether the size of the damage is increasing. The performance of the developed system was validated through a field test, demonstrating that the system can enhance convenience by accelerating the inspector's essential tasks such as detecting damages, measuring their size, manually recording their information, and locating previous damages.

• Computational Structural Engineering
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• v.5 no.3
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• pp.119-126
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• 1992

Most civil engineering structures such as bridges, power plants, and offshore platforms are apt to suffer structural damages over their service lives caused by adverse loadings, such as earthquakes, wind and wave forces. Accumulation of structural damages over a long period of time might cause catastrophic structural failure. Therefore, a methodology for monitoring the structural integrity is essential for assuring the safety of the existing structures. A method for the damage assessment of structures by the second order inverse modal perturbation technique is presented in this paper. Perturbation equation consists of a matrix equation involving matrices of structural changes(stiffness and mass matrix changes) and matrices of modal property changes(natural frequency and mode shape changes). The damages of a structure are represented as changes in the stiffness matrix. In this study, a second order perturbation equation is formulated for the damage assessment of structures, and solved by an iterative procedure. The effectiveness of the proposed method has been investigated through a series of example analysis. The estimated results for the structural damage indicated that the present method yields resonable estimates for the structural changes.

• Structural Engineering and Mechanics
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• v.60 no.4
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• pp.729-747
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• 2016

This study aims to present a novel optimization algorithm known as gravitational search algorithm (GSA) for structural damage detection. An objective function for damage detection is established based on structural vibration data in frequency domain, i.e., natural frequencies and mode shapes. The feasibility and efficiency of the GSA are testified on three different structures, i.e., a beam, a truss and a plate. Results show that the proposed strategy is efficient for determining the locations and the extents of structural damages using the first several modal data of the structure. Multiple damages cases in different types of structures are studied and good identification results can be obtained. The effect of measurement noise on the identification results is investigated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.914-921
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• 2006

To describe the effect of the numerous and various oriented microcracks on the compressive and tensile concrete behaviors, the directional nonlocality is defined. The plasticity model using multiple failure criteria is developed for RC planar members in tension-compression. The crack damages are defined in the pre-determined reference orientations, and then the total crack damage is calculated by integrating multi-oriented crack damages. To describe the effect of directional nonlocality on the anisotropic tensile damage, based on the existing test results, the nonlocal damage factor is defined in each reference orientation. The reduced compressive strength in the cracked concrete is defined by the multi-oriented crack damages defined as excluding the tensile normal plastic strain from the compressive equivalent plastic strain. The proposed model is implemented to finite element analysis, and it is verified by comparisons with various existing panel test results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.9
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• pp.884-891
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• 2009

This study investigates some of swarm intelligence algorithms to tackle a traditional damage detection problem having stiffness degradation or damage in mechanical structures. Particle swarm(PSO) and ant colony optimization(ACO) methods have been exploited for localizing and estimating the location and extent damages in a structure. Both PSO and ACO are population-based, stochastic algorithms that have been developed from the underlying concept of swarm intelligence and search heuristic. A finite element (FE) model updating is implemented to minimize the difference in a set of natural frequencies between measured and baseline vibration data. Stiffness loss of certain elements is considered to simulate structural damages in the FE model. It is numerically shown that PSO and ACO algorithms successfully completed the optimization process of model updating in locating unknown damages in a truss structure.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Smart Structures and Systems
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• v.7 no.2
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• pp.117-132
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• 2011

This paper is aimed at presenting two methods on the basis of pattern search and genetic algorithms to detect and estimate damage in plates using the modal data of a damaged plate. The proposed methods determine the damages of plate structures using optimization of an objective function by pattern search and genetic algorithms. These methods have been applied to two numerical examples, namely four-fixed supported and cantilever plates with and without noise in the modal data and containing one or several damages. The obtained results clearly reveal that the proposed methods can be viewed as a powerful and reliable method for structural damage detection in plates using the modal data.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.322-327
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• 2004

This paper describes the structural analysis result of accident EMU(Electric Multiple Units). Structural analysis of EMU was performed for the criteria of safety assessment. Structural analysis using commercial I-DEAS software provided important information on the stress distribution and load transfer mechanisms as well as the amount of damages during rolling stock crash. Tensile tests were performed on two different types of specimens in order to evaluate the strength changes before and after damages, obtained from plastic deformed area and nondeformed region of the accident EMU. The structural analysis and tensile test results have been used to provide the critical information for the criteria of safety assessment.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.366-373
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• 2003

This paper introduces a frequency-domain method of structural damage identification. It is formulated in a general form to include the nonlinearity of damage magnitudes from the dynamic stiffness equation of motion for a beam structure. The appealing features of the present damage identification method are: (1) it requires only the frequency response functions measured from damaged structure as the input data, and (2) it can locate and quantify many local damages at the same time. The feasibility of the present damage identification method is tested through some numerically simulated damage identification analyses for a cantilevered beam with three piece-wise uniform damages.

• Structural Engineering and Mechanics
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• v.53 no.2
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• pp.249-260
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• 2015

Damage detection based on a reference set of measured data usually has the problem of different environmental temperature in the two sets of measurements, and the effect of temperature difference is usually ignored in the subsequent model updating. This paper attempts to identify the structural damage including the temperature difference with artificial measurement noise. Both local damages and the temperature difference are identified in a gradient-based model updating method based on dynamic response sensitivity. The sensitivities of dynamic response with respect to the system parameters and temperature difference are calculated by direct integration method. The measured dynamic responses of the structure from two different states are used directly to identify the structural local damages and the temperature difference. A single degree-of-freedom mass-spring system and a planar truss structure are studied to illustrate the effectiveness of the proposed method.