• Smart Structures and Systems
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• v.8 no.3
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• pp.253-274
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• 2011

In this paper, the harmonic displacement response of a damaged square plate with all-over part-through damage parallel to one edge is utilized as the input signal function in wavelet analysis. The method requires the properties of the damaged plate, i.e., no information about the original undamaged structure is required. The location of damage is identified by sudden changes in the spatial variation of transformed response. The incurred damage causes a change in the stiffness or mass of the plate. This causes a localized singularity which can be identified by a wavelet analysis of the displacement response. In this study via numerical examples shown by using harmonic response is more versatile and effective compared with the static deflection response, specially in the presence of noise. In the light of the obtained results, suggestions for future work are presented and discussed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.95-102
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• 2003

To define an analytical model for a structural system or to assess damage in the system, system identification(SI) methods have been developed and widely applied. The paper presents a method of determining optimal sensor location(OSL) based on the maximum likelihood approach, which is applicable to modal SI methods. To estimate unknown parameters reliably, it is necessary that the information provided by the experiment should be maximized. By applying the Cramer-Rao inequality, a Fisher information matrix in terms of the probability density function of measurements is obtained from a lower bound of the estimation error. The paper also proposes a scheme of determining of OSL on damaged structures by using maximum strain energy factor. Simulation studies have carried out to investigate the proposed OSL algorithm for both undamaged and damaged structures.

• Structural Monitoring and Maintenance
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• v.1 no.3
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• pp.339-356
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• 2014

This study has been motivated to evaluate the practicality of numerical simulation of impedance monitoring for damage detection in steel column connection. In order to achieve the objective, the following approaches are implemented. Firstly, the theory of electro-mechanical (E/M) impedance responses and impedance-based damage monitoring method are outlined. Secondly, the feasibility of numerical simulation of impedance monitoring is verified for several pre-published experimental examples on steel beams, cracked aluminum beams, and aluminum round plates. Undamaged and damaged steel and aluminum beams are simulated to compare to experimental impedance responses. An aluminum round plate with PZT patch in center is simulated to investigate sensitive range of impedance responses. Finally, numerical simulation of the impedance-based damage monitoring is performed for a steel column connection in which connection bolts are damaged. From the numerical simulation test, the applicability of the impedance-based monitoring to the target steel column connection can be evaluated.

• Smart Structures and Systems
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• v.18 no.5
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• pp.839-864
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• 2016

This paper presents an efficient method for updating the structural finite element model. Model updating is performed through minimizing the difference between the recorded acceleration of a real damaged structure and a hypothetical damaged one. This is performed by updating physical parameters (module of elasticity in this study) in each step using iterative process of modified nonlinear conjugate gradient (M-NCG) and modified Broyden-Fletcher-Goldfarb-Shanno algorithm (M-BFGS) separately. These algorithms are based on sensitivity analysis and provide a solution for nonlinear damage detection problem. Three illustrative test examples are considered to assess the performance of the proposed method. Finally, it is demonstrated that the proposed method is satisfactory for detecting the location and ratio of structural damage in presence of noise.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.779-788
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• 2017

System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.2
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• pp.19-27
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• 2002

The early damage detection of large structures is very important to prevent the disaster due to its global failure. In this paper, a crack detection method of the beam-analogy structure based on the wavelet transformation of mode shape is presented. The method can effectively detect the singularity of mode shape caused to the inconsistency of bending moment and shear force at the damaged part using the discrete wavelet of mode shape and its inverse transforms of detail components. To investigate the validity and the applicability of the presented damage detection method, numerical simulation and experiment are carried out for the idealized beam and the real ship structures.

• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.77-91
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• 2011

A simply structural damage detection software is developed to identification damage in beams. According to linear fracture mechanics theory, the localized additional flexibility in damage vicinity can be represented by a lumped parameter element. The damaged beam is modeled by wavelet-based elements to gain the first three frequencies precisely. The first three frequencies influencing functions of damage location and depth are approximated by means of surface-fitting techniques to gain damage detection database of forward problem. Then the first three measured natural frequencies are employed as inputs to solve inverse problem and the intersection of the three frequencies contour lines predict the damage location and depth. The DLL (Dynamic Linkable Library) file of damage detection method is coded by C++ and the corresponding interface of software is coded by virtual instrument software LabVIEW. Finally, the software is tested on beams and shafts in engineering. It is shown that the presented software can be used in actual engineering structures.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.29-39
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• 2020

Forest fire is a critical disaster that causes massive destruction of forest ecosystem and economic loss. Hence, accurate estimation of the burned area is important for evaluation of the degree of damage and for preparing baseline data for recovery. Since most of the area size damaged by wildfires in Korea is less than 1 ha, it is necessary to use satellite or drone images with a resolution of less than 10m for detecting the damage area. This paper aims to detect wildfire-damaged area from a Kompsat-3 image using the indices such as NDVI (normalized difference vegetation index) and FBI (fire burn index) and to examine the classification characteristics according to the methods such as Otsu thresholding and ISODATA(iterative self-organizing data analysis technique). To mitigate the salt-and-pepper phenomenon of the pixel-based classification, a gaussian filter was applied to the images of NDVI and FBI. Otsu thresholding and ISODATA could distinguish the burned forest from normal forest appropriately, and the salt-and-pepper phenomenon at the boundaries of burned forest was reduced by the gaussian filter. The result from ISODATA with gaussian filter using NDVI was closest to the official record of damage area (56.9 ha) published by the Korea Forest Service. Unlike Otsu thresholding for binary classification,since the ISODATA categorizes the images into multiple classes such as(1)severely burned area, (2) moderately burned area, (3) mixture of burned and unburned areas, and (4) unburned area, the characteristics of the boundaries consisting of burned and normal forests can be better expressed. It is expected that our approach can be utilized for the high-resolution images obtained from other satellites and drones.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.201-214
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• 2020

This study aimed to early detect damaged trees by pine wilt disease using the vegetation indices of UAV images. The location data of 193 pine wilt disease trees were constructed through field surveys and vegetation index analyses of NDVI, GNDVI, NDRE and SAVI were performed using multi-spectral UAV images at the same time. K-Means algorithm was adopted to classify damaged trees and confusion matrix was used to compare and analyze the classification accuracy. The results of the study are summarized as follows. First, the overall accuracy of the classification was analyzed in order of NDVI (88.04%, Kappa coefficient 0.76) > GNDVI (86.01%, Kappa coefficient 0.72) > NDRE (77.35%, Kappa coefficient 0.55) > SAVI (76.84%, Kappa coefficient 0.54) and showed the highest accuracy of NDVI. Second, K-Means unsupervised classification method using NDVI or GNDVI is possible to some extent to find out the damaged trees. In particular, this technique is to help early detection of damaged trees due to its intensive operation, low user intervention and relatively simple analysis process. In the future, it is expected that the utilization of time series images or the application of deep learning techniques will increase the accuracy of classification.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.253-265
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• 2020

As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.