• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.9
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• pp.884-891
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• 2009

This study investigates some of swarm intelligence algorithms to tackle a traditional damage detection problem having stiffness degradation or damage in mechanical structures. Particle swarm(PSO) and ant colony optimization(ACO) methods have been exploited for localizing and estimating the location and extent damages in a structure. Both PSO and ACO are population-based, stochastic algorithms that have been developed from the underlying concept of swarm intelligence and search heuristic. A finite element (FE) model updating is implemented to minimize the difference in a set of natural frequencies between measured and baseline vibration data. Stiffness loss of certain elements is considered to simulate structural damages in the FE model. It is numerically shown that PSO and ACO algorithms successfully completed the optimization process of model updating in locating unknown damages in a truss structure.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.1
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• pp.53-59
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• 2014

In multiple object tracking, accurate detection for each of objects that appear sequentially and effective tracking in complicated cases that they are overlapped with each other are very important. In this paper, we propose a multiple object tracking system that has a concrete detection and tracking characteristics by using multi-lateral histogram and SIFT feature extraction algorithm. Especially, by limiting the matching area to object's inside and by utilizing the location informations in the keypoint matching process of SIFT algorithm, we advanced the tracking performance for multiple objects. Based on the experimental results, we found that the proposed tracking system has a robust tracking operation in the complicated environments that multiple objects are frequently overlapped in various of directions.

• International Journal of Contents
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• v.8 no.1
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• pp.30-38
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• 2012

Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.263-273
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• 1996

The time instants, at which QRS complexes are detected, are used in the electrocardioyam rhythm analysis. Hence, it is necessary that all QRS complexes are detected and that no other waves or artifacts are wrongly labeled as such. These time instants are also used in other tasks as an indication of the location of significant events in the ECG. For example, the QRS typification algorithm uses these points to define the region of interest for complex comparison and alignment. When waveform recognition is drone for each complex, these points are used to define search intervals in which the onset and the end of the QRS nmplex have to be found This paper proposes the method for the detection of QRS complexes and decision rule for the classification scheme. The efficiency of the detection is demonstrated with the aid of an internationally validated CSE(Common Standard for Quantitative Electrocardioyaph) data set 3 and 4.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.4
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• pp.371-382
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• 2001

The recognition of such natural wave guides as plates, rods, hollow cylinders, multi-layer structures or simply an interface between two materials combined with an increased understanding of the physics and wave mechanics of guided wave propagation has led to a significant increase in the number of guided wave inspection applications being developed each year. Of primary attention Is the ability to inspect partially hidden structures, hard to access areas, and teated or insulated structures. An introduction to some physical consideration of guided waves followed by some sample problem descriptions in pipe, ice detection, fouling detection in the foods industry, aircraft, tar coated structures and acoustic microscopy is presented in this paper. A sample problem in Boundary Element Modeling is also presented to illustrate the move in guided wave analysis beyond detection and location analysis to quantification.

• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.30-35
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• 2005

This study proposes construction of through transmission for weld defects detection of rail weld zone from ultrasonic signals. For these purposes, the ultrasonic signals for defects(porosity and crack) of weld zone in rails are acquired in the type of time series data and echo strength. 6 lines in the distance amplitude characteristics curve(DACC) indicated damage evaluation standard of weld zone in rails. The acquired ultrasonic signals agree flirty well with the mesured results of reference block and sensitivity block(defect location beam propagation distance, echo strength, etc). The proposed construction of through transmission in this study can be used for weld defects detection of rail weld zone.

• Smart Structures and Systems
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• v.2 no.3
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• pp.275-293
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• 2006

For health monitoring purpose usually the structure is instrumented with a large scale and multichannel measurement system. In case of highway bridges, operating vehicle could be utilized to reduce the number of measuring devices. First this paper presents a static damage detection algorithm of using operating vehicle load. The technique has been validated by finite element simulation and simple laboratory test. Next the paper presents an approach of using this technique to field application. Here operating vehicle load data has been used by instrumenting the bridge at single location. This approach gives an upper hand to other sophisticated global damage detection methods since it has the potential of reducing the measuring points and devices. It also avoids the application of artificial loading and interruption of any traffic flow.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1253-1270
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• 2015

In this paper Magnetic Charged System Search (MCSS) and Particle Swarm Optimization (PSO) are applied to the problem of damage detection using frequencies and mode shapes of the structures. The objective is to identify the location and extent of multi-damage in structures. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including two beams and two trusses are considered. A comparison between the PSO and MCSS is conducted to show the efficiency of the MCSS in finding the global optimum. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1229-1234
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• 2004

Accurate and reliable tracking system is essential for the central train control system. There are two systems widely being used. one is the fixed block system which utilizes the track circuit for the detection of train position. the other is the moving block system which has the advantage over the former since it enables shorter radio signal for the train position detection. In this paper a new algorithm is proposed which uses signal's phase difference of arrival to detect the train position. Experimental verification of the algorithm is presented in the paper.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.880-887
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• 2005

This paper presents a fault diagnosis(detection and isolation) approach for the Ammunition Transport Automation system(ATAS). Due to limited time and information available during its cyclic operation, the on-line fault detection algorithm consists of sequential test logics referring to the normal states, which can be considered as a kind of expert system. If a failure were detected, the off-line isolation algorithm finds the fault location through trained ART2 neural network. By the results of simulations and some on-line field test, it has been shown that the presented approach is effective enough and applicable to related automation systems.