• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.1
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• pp.124-132
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• 2013

Damage location and extent could be detected by the inverse analysis on dynamic response of the damaged structure. In general, detection of damage location is possible by the observation of the mode shape difference between undamaged and damaged structure and assessment of stiffness reduction is possible by the observation of the natural frequency difference of them. The study on damage detection by the dynamic response in civil structures is reported enough and in practical use, but in building structures it is reported seldom due to several problems. The purpose of this study is to present the damage detection method on shear building structures by mode shape. The damage location index using 1st mode shape is observed theoretically to find out damage location. The damage detection method is applied to numerical analysis model such as MATLAB and MIDAS GENw for the verification. Finally the shaking table test on 3 story shear building is performed for the examination of the damage detection method. In shaking table results, as the story stiffness decrease by 25% the 1st mode frequency increase by 12%, and the damage location index represents minus at damaged story.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.71-82
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• 2012

In this paper, we propose a license plate detection method with improved Adaboost learning and MCT (Modified Census Transform). The MCT represents the local structure patterns as integer numbered feature values which has robustness to illumination change and memory efficiency. However, since these integer values are discrete, a lookup table is needed to design a weak classifier for Adaboost learning. Some previous research efforts have focused on minimization of exponential criterion for Adaboost optimization. In this paper, a method that uses MCT and improved Adaboost learning based on Newton's optimization to exponential criterion is proposed for license plate detection. Experimental results on license patch images and field images demonstrate that the proposed method yields higher performance of detection rates with low false positives than the conventional method using the original Adaboost learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4307-4325
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• 2016

With the aim of solving the problems of long processing times, high memory consumption and low event throughput in the current processing approaches in out-of-order RFID event streams, an efficient complex event processing method based on INFA-HTS (Improved Nondeterministic Finite Automaton-Hash Table Structure) is presented in this paper. The contribution of this paper lies in the fact that we use INFA and HTS to successfully realize the detection of complex events for out-of-order RFID event streams. Specifically, in our scheme, to detect the disorder of out-of-order event streams, we expand the traditional NFA model into a new INFA model to capture the related RFID primitive events from the out-of-order event stream. To high-efficiently manage the large intermediate capturing results, we use the HTS to store and process them. As a result, these problems in the existing methods can be effectively solved by our scheme. The simulation results of our experiments show that our proposed method in this paper outperforms some of the current general processing approaches used to process out-of-order RFID event streams.

• Convergence Security Journal
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• v.13 no.4
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• pp.41-46
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• 2013

Routing protocol using in the existing wire network cannot be used as it is for efficient data transmission in MANET. Because it consists of only mobile nodes, network topology is changing dynamically. Therefore, each mobile node must perform router functions. Variety of routing attack like DoS in MANET is present owing to these characteristic. In this paper, we proposed cooperative-based detection method to improve detection performance of flooding attack which paralyzes network by consuming resource. Accurate attack detection is done as per calculated adaptively threshold value considered the amount of all network traffic and the number of nodes. All the mobile nodes used a table called NHT to perform collaborative detection and apply cluster structure to the center surveillance of traffic.

• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.555-574
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• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.

• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.1-20
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• 2011

This study investigates the feasibility of detecting structural damage using the HHT method. A damage detection index, the ratio of bandwidth (RB) is proposed. This index is highly correlated or approximately equal to the change of equivalent damping ratio for an intact structure incurring damage from strong ground motions. Based on an analysis of shaking table test data from benchmark models subjected to adjusted Kobe and El Centro earthquakes, the damage detection index is evaluated using the Hilbert-Huang Transform (HHT) and the Fast Fourier Transform (FFT) methods, respectively. Results indicate that, when the response of the structure is in the elastic region, the RB value only slightly changes in both the HHT and the FFT spectra. Additionally, RB values estimated from the HHT spectra vs. the PGA values change incrementally when the structure response is nonlinear i.e., member yielding occurs, but not in the RB curve from the FFT spectra. Moreover, the RB value of the top floor changes more than those from the other floors. Furthermore, structural damage is detected only when using the acceleration response data from the top floor. Therefore, the ratio of bandwidth RB estimated from the smoothed HHT spectra is an effective and sensitive damage index for detecting structural damage. Results of this study also demonstrate that the HHT is a powerful method in analyzing the nonlinear responses of steel structures to strong ground motions.

• Smart Structures and Systems
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• v.8 no.1
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• pp.119-137
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• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.930-935
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• 2014

A Gabor filter is a linear filter used for edge detectionas frequency and orientation representations of Gabor filters are similar to those of the human visual system. In this thesis, we propose a pedestrian detection algorithm using a Gabor filter bank. In order to extract the features of the pedestrian, we use various image processing algorithms and data structure algorithms. First, color image segmentation is performed to consider the information of the RGB color space. Second, histogram equalization is performed to enhance the brightness of the input images. Third, convolution is performed between a Gabor filter bank and the enhanced images. Fourth, statistical values are calculated by using the integral image (summed area table) method. The calculated statistical values are used for the feature matrix of the pedestrian area. To evaluate the proposed algorithm, the INRIA pedestrian database and SVM (Support Vector Machine) are used, and we compare the proposed algorithm and the HOG (Histogram of Oriented Gradient) pedestrian detector, presentlyreferred to as the methodology of pedestrian detection algorithm. The experimental results show that the proposed algorithm is more accurate compared to the HOG pedestrian detector.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Earthquakes and Structures
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• v.17 no.6
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• pp.599-609
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• 2019

After an earthquake, a quick seismic assessment of a structure can facilitate the recovery of operations, and consequently, improve structural resilience. Especially for facilities that play a key role in rescue or refuge efforts (e.g., hospitals and power facilities), or even economically important facilities (e.g., high-tech factories and financial centers), immediately resuming operations after disruptions resulting from an earthquake is critical. Therefore, this study proposes a prompt post-earthquake seismic evaluation method that uses displacement and acceleration measurements taken from real structural responses that resulted during an earthquake. With a prepared pre-earthquake capacity curve of a structure, the residual seismic capacity can be estimated using the residual roof drift ratio and stiffness. The proposed method was verified using a 6-story steel frame structure on a shaking table. The structure was damaged during a moderate earthquake, after which it collapsed completely during a severe earthquake. According to the experimental results, a reasonable estimation of the residual seismic capacity of structures can be performed using the proposed post-earthquake seismic evaluation method.