• Earthquakes and Structures
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• v.8 no.4
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• pp.935-956
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• 2015

Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.

• Geomechanics and Engineering
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• v.9 no.6
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• pp.729-742
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• 2015

The aim of the present work was the study of instability in a loose sand from Les Dunes beach in Ain Beninan, Algeria, where the Boumerdes earthquake occurred in 2003. This earthquake caused significant structural damages and claimed the lives of many people. Damages caused to infrastructures were strongly related to phenomena of liquefaction. The study was based on the results of two drained and six undrained triaxial tests over a local sand collected in a region where liquefaction occurred. All the tests hereby analyzed followed compression stress-paths in monotonic conditions and the specimens were isotropically consolidated, since the objective was to study the instability due to static loading as part of a more general project, which also included cyclic studies. The instability was modeled with the second-order work increment criterion. The definition of the instability line for Les Dunes sand and its relation with yield surfaces allowed the identification of the region of potential instability and helped in the evaluation of the susceptibility of soils to liquefy under undrained conditions and its modeling. The dilatancy rate was studied in the points where instability began. Some mixed tests were also simulated, starting with drained conditions and then changing to undrained conditions at different time steps.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.799-808
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• 2023

Globally, abnormal climate phenomena have led to an increase in rainfall intensity, consequently causing a rise in flooding-related damages. Agricultural areas, in particular, experience significant annual losses every year due to a lack of research on flooding in these regions. This study presents a comprehensive analysis of the flood event that occurred on July 16, 2017, in the agricultural area situated in Sindaedong, Heungdeok-gu, Cheongju-si. To achieve this, the EPA (United States Environmental Protection Agency) Storm Water Management Model (SWMM) was employed to generate runoff data by rainfall information. The produced runoff data facilitated the identification of flood occurrence points, and the analysis results exhibited a strong correlation with inundation trace maps provided by the Ministry of the Interior and Safety (MOIS). The detailed output of the SWMM model enabled the extraction of time-specific runoff information at each inundation point, allowing for a detailed understanding of the inundation status in the agricultural area over different time frames. This research underscores the significance of utilizing the SWMM model to simulate inundation in agricultural areas, thereby validating the efficacy of flood alerts and risk management plans. In particular, the integration of rainfall data and the SWMM model in flood prediction methodologies is expected to enhance the formulation of preventative measures and response strategies against flood damages in agricultural areas.

• Journal of Korean Society of Steel Construction
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• v.17 no.2 s.75
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• pp.173-181
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• 2005

This study deals with a method to identify damages of free vibrating thin plate structures using the combined finite element method (FEM) and the advanced uniform micro-genetic algorithm.To solve the inverse problem using the combined method, this study uses several natural frequencies instead of mode shapes in a structure as the measured data. The technique described in this paper allows us not only to detect the damaged elements but also to find their numbers, locations, and the extent of damage.To demonstrate the feasibility of the proposed method, the algorithm is applied to a free vibrating steel thin plate structures with arbitrary damages. From the standpoint of computation efficiency, the proposed method in this study has advantages when compared with the existing simple genetic algorithms. The numerical examples demonstrate that the method using micro-genetic algorithms can possibly detect correctly the damages of thin plates from only several natural frequencies instead of their natural modes.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.3
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• pp.9-20
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• 1999

A method is proposed to estimate the joint damages of a steel structure from modal data using the neural networks technique. The beam-to-column connection in a steel frame structure is represented by a zero-length rotational spring of the end of the beam element, and the connection fixity factor is defined based on the rotational stiffness so that the factor may be in the range 0~1.0. Then, the severity of joint damage is defined as the reduction ratio of the connection fixity factor. Several advanced techniques are employed to develop the robust damage identification technique using neural networks. The concept of the substructural indentification is used for the localized damage assessment in the large structure. The noise-injection learning algorithm is used to reduce the effects of the noise in the modal data. The data perturbation scheme is also employed to assess the confidence in the estimated damages based on a few sets of actual measurement data. The feasibility of the proposed method is examined through a numerical simulation study on a 2-bay 10-story structure and an experimental study on a 2-story structure. It has been found that the joint damages can be reasonably estimated even for the case where the measured modal vectors are limited to a localized substructure and the data are severely corrupted with noise.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.6
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• pp.147-154
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• 2014

The cable damages of the bridge structures induce very important impact on the structural safety, which implies the close monitoring of the cable damage is required to secure sustained safety of the bridges. Most usual available maintenance techniques are based on the monitoring the change of the natural frequency of the structures by damages. However, existing method are based on vibration method to calculate lateral vibration and system identification can calculate the axial stiffness using sensitivity equation by trial error method. But the frequency study by the longitudinal movement need because of the sag effect in system identification. This study proposes a new method to investigate the damage magnitudes and status. The method improves the accuracies in the magnitudes and status of damages by adopting the natural frequency of longitudinal movement. The study results have been validated by comparing them with the approximate solution of FEM. Thus, the relationship of cable damage and frequency appear with relation that the severe damage has the little frequency. If we know the real frequency we can estimate the cable damage severity using this relationship. This method can be possible the efficient management of the cable damage.

• Smart Structures and Systems
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• v.20 no.2
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• pp.247-261
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• 2017

In the field of dynamic measurement and structural damage identification, it is generally known that modal frequencies may be measured with higher accuracy than mode shapes. However, the number of natural frequencies within a measurable range is limited. Accessing additional forms of modal frequencies is thus desirable. The present study is concerned about the extraction of artificial boundary condition (ABC) frequencies from modal testing. The ABC frequencies correspond to the natural frequencies of the structure with a perturbed boundary condition, but they can be extracted from processing the frequency response functions (FRF) measured in a specific configuration from the structure in its existing state without the need of actually altering the physical support condition. This paper presents a comprehensive experimental investigation into the measurability of the ABC frequencies from physical experiments. It covers the testing procedure through modal testing, the data processing and data analysis requirements, and the FRF matrix operations leading to the extraction of the ABC frequencies. Specific sources of measurement errors and their effects on the accuracy of the extracted ABC frequencies are scrutinised. The extracted ABC frequencies are subsequently applied in the damage identification in beams by means of finite element model updating. Results demonstrate that it is possible to extract the first few ABC frequencies from the modal testing for a variety of artificial boundary conditions incorporating one or two virtual pin supports, and the inclusion of ABC frequencies enables the identification of structural damages without the need to involve the mode shape information.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.131-137
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• 2014

Although illegal reproduction of cartoon books are prevalent with rapid growth of webhard services and smartphone use, fingerprinting technology for product identification, as seen in music and videos, has not been developed yet. This leads to indiscriminate illegal reproduction of cartoon books, causing great amount of copyright damages from copyright infringement of the rightful owners. The copyright R&D project granted from the Korea Copyright Permission (Project Title: Identification and Copy Protection Technology of Bookscaned Text/Comic Books) has been carried out in order to develop technology to effectively identify illegal reproduction and distribution of scanned cartoon books. The developed technology will contribute to increase of royalty payments and robust ecosystem of cartoon book markets. The study is to propose an enhanced implementation model for identification of scanned cartoon books on the basis of hierarchical symmetric difference feature algorithms adopted from existing feature extraction algorithms for video.

• Smart Structures and Systems
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• v.31 no.4
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• pp.421-436
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• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.