• Smart Structures and Systems
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• v.19 no.4
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• pp.449-461
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• 2017

One of the most recent methods of structural damage identification is using the difference between structures responses after and before damage occurrence. To do this one can formulate the damage detection problem as an inverse optimization problem where the extents of damage in each element are considered as the optimizations variables. To optimize the objective function, heuristic methods such as GA, PSO etc. are widely utilized. In this paper, inspired by animals such as bat, dolphin, oilbird, shrew etc. that use echolocation for finding food, a new and efficient method, called Echolocation Search Algorithm (ESA), is proposed to properly identify the site and extent of multiple damage cases in structural systems. Numerical results show that the proposed method can reliably determine the location and severity of multiple damage cases in structural systems.

• Smart Structures and Systems
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• v.17 no.2
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• pp.347-361
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• 2016

A two-stage method for damage detection in truss systems is proposed. In the first stage, a modal residual vector based indicator (MRVBI) is introduced to locate the potentially damaged elements and reduce the damage variables of a truss structure. Then, in the second stage, a differential evolution (DE) based optimization method is implemented to find the actual site and extent of damage in the structure. In order to assess the efficiency of the proposed damage detection method, two numerical examples including a 2D-truss and 3D-truss are considered. Simulation results reveal the high performance of the method for accurately identifying the damage location and severity of trusses with considering the measurement noise.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.300-307
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• 2002

Damage estimation methods are classified into two groups according to the dependence on the FE model : signal-based and model-based methods. Signal-based damage estimation methods are generally appropriate for detection of damage location, whereas not effective for estimation of damage severities. Model-based damage estimation methods are difficult to apply directly to the structures with a large number of the probable damaged members. It is difficult to obtain the exact model representing the real bridge behavior due to the modeling errors. The modeling errors even may exceed the modal sensitivity on damage. In this study, Model-based damage detection method which can effectively consider the modeling errors is suggested. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness of the presented method.

• Structural Engineering and Mechanics
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• v.8 no.3
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• pp.285-297
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• 1999

A method is presented to find the location and magnitude of damage in a structure using data from dynamic tests. The test data include a combination of natural frequency measurements, taken before and after the occurrence of damage, and response measurements taken after damage. An algorithm is developed to identify localized increases in the flexibility of the structural members. Increases in flexibility are attributed to damage. The algorithm uses the sensitivity of the flexibility matrix to changes in the natural frequencies of the structure to identify the damage. A set of under determined equations is solved using an objective function which is derived from measurements of the system moments. Damage ranging from 10 to 60% increase in the flexibility of a member was successfully identified in a 50 d.o.f. structure, using a small number of natural frequency and velocity measurements.

• Structural Engineering and Mechanics
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• v.33 no.3
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• pp.325-337
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• 2009

Structural damage detection, damage localization and severity estimation of jacket platforms, based on calculating modal strain energy is presented in this paper. In the structure, damage often causes a loss of stiffness in some elements, so modal parameters; mode shapes and natural frequencies, in the damaged structure are different from the undamaged state. Geometrical location of damage is detected by computing modal strain energy change ratio (MSECR) for each structural element, which elements with higher MSECR are suspected to be damaged. For each suspected damaged element, by computing cross-modal strain energy (CMSE), damage severity as the stiffness reduction factor -that represented the ratios between the element stiffness changes to the undamaged element stiffness- is estimated. Numerical studies are demonstrated for a three dimensional, single bay, four stories frame of the existing jacket platform, based on the synthetic data that generated from finite element model. It is observed that this method can be used for damage detection of this kind of structures.

• Smart Structures and Systems
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• v.22 no.6
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• pp.699-709
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• 2018

With increasing traffic volumes and rising vehicle traffic, especially in cities, the number of pedestrian bridges has also increased significantly. Like all other structures, pedestrian bridges also suffer damage. In order to increase the safety of pedestrians, it is necessary to identify existing damage and to repair them to ensure the safety of the bridge structures. Owing to the shortcomings of local methods in identifying damage and in order to enhance the reliability of detection and identification of structural faults, signal methods have seen significant development in recent years. In this research, a new methodology, based on cone-shaped kernel distribution with a new damage index, has been used for damage detection in pedestrian truss bridges. To evaluate the proposed method, the numerical models of the Warren Type steel truss and the Arregar steel footbridge were used. Based on the results, the proposed method and damage index identified the damage and determined its location with a high degree of precision. Given the ease of use, the proposed method can be used to identify faults in pedestrian bridges.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Structural Engineering and Mechanics
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• v.40 no.5
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• pp.719-743
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• 2011

A hybrid damage monitoring scheme using parallel acceleration-impedance approaches is proposed to detect girder damage and support damage in steel plate-girder bridges which are under ambient train-induced excitations. The hybrid scheme consists of three phases: global and local damage monitoring in parallel manner, damage occurrence alarming and local damage identification, and detailed damage estimation. In the first phase, damage occurrence in a structure is globally monitored by changes in vibration features and, at the same moment, damage occurrence in local critical members is monitored by changes in impedance features. In the second phase, the occurrence of damage is alarmed and the type of damage is locally identified by recognizing patterns of vibration and impedance features. In the final phase, the location and severity of the locally identified damage are estimated by using modal strain energy-based damage index methods. The feasibility of the proposed scheme is evaluated on a steel plate-girder bridge model which was experimentally tested under model train-induced excitations. Acceleration responses and electro-mechanical impedance signatures were measured for several damage scenarios of girder damage and support damage.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.6
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• pp.251-259
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• 2021

Current seismic fragility functions for buildings were developed by defining damage state threshold based on story drift concerning foreign references and using the capacity spectrum method based on spectral displacement. In this study, insufficient details and dependence on the core location of piloti-type buildings were not reflected in the fragility function because it was developed before the Pohang earthquake. In order to develop an improved one for piloti-type buildings, several types of core were selected, damage state threshold was determined based on the capacity of structural members, and three-dimensional analyses were utilized. As a result, seismic fragility functions based on spectral acceleration were developed for various core locations and different shear strengths of the column stirrup. The fragility of piloti-type buildings significantly varied according to core location, an additional single wall, and whether the contribution of column stirrup was included or not. To estimate fragility more reasonably, it is necessary to prepare the parameters to reflect actual state well.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.455-461
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• 2020

Electronic payment system using Internet banking is a very important application for users of e-commerce environment. With rapidly growing use of fintech applications, the risk and damage caused by malicious hacking or identity theft are getting significant. To prevent the damage, fraud detection system (FDS) calculates the risk of the electronic payment transactions using user profiles including types of goods, device status, user location, and so on. In this paper, we propose a new risk calculation method using relative location of users such as SSID of wireless LAN AP and MAC address. Those relative location information are more difficult to imitate or copy compared with conventional physical location information like nation, GPS coordinates, or IP address. The new method using relative location and cumulative user characteristics will enable stronger risk calculation function to FDS and thus give enhanced security to electronic payment systems.