• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.4
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• pp.22-26
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• 2013

• Smart Structures and Systems
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• v.15 no.3
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• pp.593-608
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• 2015

In many of the industrialized countries an increasing amount of infrastructure is ageing. This has become specifically critical to bridges which are a major asset with respect to keeping an economy alive. Life of this infrastructure is scattering but often little quantifiable information is known with respect to its damage condition. This article describes how a damage tolerance approach used in aviation today may even be applied to civil infrastructure in the sense that operational life can be applied in the context of modern life cycle management. This can be applied for steel structures as a complete process where much of the damage accumulation behavior is known and may even be adopted to concrete structures in principle, where much of the missing knowledge in damage accumulation has to be substituted by enhanced inspection. This enhanced and continuous inspection can be achieved through robotic systems in a first approach as well as built in sensors in the sense of structural health monitoring (SHM).

• Earthquakes and Structures
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• v.8 no.4
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• pp.821-841
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• 2015

This paper proposes a two-stage imaging approach for quantitative inspection of damages in metallic plates using the fundamental anti-symmetric mode of ($A_0$) Lamb wave. The proposed approach employs a number of transducers to transmit and receive $A_0$ Lamb wave pulses, and hence, to sequentially scan the plate structures before and after the presence of damage. The approach is applied to image the corrosion damages, which are simplified as a reduction of plate thickness in this study. In stage-one of the proposed approach a damage location image is reconstructed by analyzing the cross-correlation of the wavelet coefficient calculated from the excitation pulse and scattered wave signals for each transducer pairs to determine the damage location. In stage-two the Lamb wave diffraction tomography is then used to reconstruct a thickness reduction image for evaluating the size and depth of the damage. Finite element simulations are carried out to provide a comprehensive verification of the proposed imaging approach. A number of numerical case studies considering a circular transducer network with eight transducers are used to identify the damages with different locations, sizes and thicknesses. The results show that the proposed methodology is able to accurately identify the damage locations with inaccuracy of the order of few millimeters of a circular inspection area of $100mm^2$ and provide a reasonable estimation of the size and depth of the damages.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.583-589
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• 2020

Recently, the utility of UAS (Unmanned Aerial System) for a smart farm using various sensors and ICT (Information & Communications Technology) is expected. In particular, it has proven its effectiveness as an outdoor crop monitoring method through various indices and is being studied in various fields. This study analyzes damage to crops caused by natural disasters and measures the damage area of rice plants. To this end, data is acquired using BG-NIR (Blue Green_Near Infrared Red) and RGB sensors, and image analysis and NDWI (Normalized Difference Water Index) index performed to review crop damage caused by in the rainy season. Also, point cloud data based on image analysis is generated, and damage is measured by comparing data before and after the typhoon through an inspection map. As a result of the study, the growth and rainy season damage of rice was examined through NDWI index analysis, and the damage area caused by typhoon was measured by analysis of the inspection map.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.49-56
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• 2023

This study proposed a damage location estimation method for automated image-based port infrastructure inspection. Memory efficiency was improved by calculating the homography matrix using feature detection technology and outlier removal technology, without going through the 3D modeling process and storing only damage information. To develop an algorithm specialized for port infrastructure, the algorithm was optimized through ground-truth coordinate pairs created using images of port infrastructure. The location errors obtained by applying this to the sample and concrete wall were (X: 6.5cm, Y: 1.3cm) and (X: 12.7cm, Y: 6.4cm), respectively. In addition, by applying the algorithm to the concrete wall and displaying it in the form of an exterior damage map, the possibility of field application was demonstrated.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.4
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• pp.247-256
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• 2004

The damage curves for the 2-story shear building to the impulsive rectangular loads were established with the peak load and Impulse ratio producing the critical displacement. The convolution integrations with the Impulse response matrix and the loads were used to find the responses of the building. The impulse response matrix required in the calculations of the convolution integration were found with the mode superposition method It is shown from the established damage curves that the responses of the top and bottom floor are sensitive to the magnitude and the impulse of the loads respectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.3
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• pp.167-176
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• 1999

This paper is concerned with the damage detection of existing 2 and 3-dimensional truss structures based on free vibration equation and extended Kalman filter. The local damage is characterized in terms of the stiffness degradation of damaged members. As the observed data, the natural frequencies and mode shapes of damaged truss structure model are adopted. Both location and stiffness of damaged parts of members in truss structures can be estimated by the proposed inverse solution procedure. The applicability and effectiveness of proposed inverse solution procedure are demonstrated through the numerical examples.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.4
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• pp.169-179
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• 2002

This paper presents an efficient algorithm for the estimation of damage location and severity in structure using Probabilistic Neural Network (PNN). Artificial neural network has been being used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training data for neural network learning and ambiguity in the relation of neural network architecture with convergence of solution. In this paper, PNN is used as a pattern classifier to overcome those problems in the conventional neural network. The basic idea of damage assessment algorithm proposed in this paper is that modal characteristics from a damaged structure are compared with the training patterns which represent the damage in specific element to determine how close it is to training patterns in terms of the probability from PNN. The training pattern that gives a maximum probability implies that the element used in producing the training pattern is considered as a damaged one. The proposed damage assessment algorithm using PNN is applied to a 2-span continuous beam model structure to verify the algorithm.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.211-219
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• 2023

The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration-based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high-intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.154-161
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• 2011

Rail inspection is very important as damages in rail can bring about a serious railway accident. In this paper, several real-time non-destructive technologies applied or considered to be applied to damage detection of rails are described. Some limits of existing ultrasonic testing method which has been widely used for rail inspection are discussed. Non-contact type NDE methods for rail inspection and their technical problems are also described.