• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.3
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• pp.281-287
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• 2001

For the conventional two-dimensional source location of acoustic emission (AE) based on the threshold crossing, wave velocity has to be measured in the actual structure to calculate the arrival-time difference and thus to form the two hyperbolae. Velocity is dependent on the fiber orientation, however, due to the dependence of elastic modulus on fiber orientation in anisotropic materials such as compost#e plates. This tan affect the accuracy of AE source location and make the source location procedure complicated. In this study, we propose a method to reduce the location error in anisotropic plates by using the numerical solution of nonlinear equations, where the velocity term has been removed by employing the fourth sensor. The efficiency and validity of the proposed method has also been experimentally verified.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.170-173
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• 2003

음향방출 신호를 이용하여 목재 섬유판(fiberboards)의 위치표정의 유용성 유무를 실험적으로 검증하였다 위치표정의 정확도를 향상하기 위해 신호처리 방법중의 하나인 웨이블릿 변환 디노이징 기법을 활용하여 저주파수인 대칭모드(굽힘파)를 활용하고, 고주파수인 비대칭모드(팽창파)를 제거하여 신호를 재구성함으로써 섬유관의 위치표정시 문턱값 통과방법을 사용할 때 발생하는 도달시간차를 최소화 할 수 있음을 확인하였다. 디노이징 기법을 활용한 섬유판의 위치 표정과 굽힘강도에 대한 사상총수를 기초로 하여 목재 구조물 및 문화재의 건전성을 평가 할 수 있을 것으로 기대된다.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.490-500
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• 2000

A new technique for the source location of acoustic emission (AE) in plates whose thichness are close to or thinner than the wavelength has been studied by introducing wavelet transform de-noising technique. The detected AE signals were pre-processed using wavelet transform to be decomposed into the low-frequency, high-amplitude flexural components and the high-frequency, low-amplitude extensional components. If the wavelet transform de-noising was employed, we could successfully filter out the extensional wave component, one of the critical errors of source location in plates by arrival time difference method. The accuracy of source location appeared to be significantly improved and independent of the setting of gain and threshold, plate thickness, sensor-to-sensor distance, and the relative position of source to sensors. Since the method utilizes the flexural component of relatively high amplitude, it could be applied to very large, thin-walled structures in practice.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.439-444
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• 2003

Acoustic emission(AE) ran be very effectively applied to locate the damaged area in large structures by detecting the elastic waves generated during the damage process within solids. Source location in the composite structures has been, however, extremely difficult due to the acoustic anisotropy with the velocity dependence on fiber orientations. In this study, it has been shown that a newly proposed method for 2-D source location of anisotropic structures is practically applicable to the real structure. The method employes wave velocities obtained with different velocities from $0^{\circ}\;to\;90^{\circ}$ for a filament wound composite pressure vessel under the air-filled and the water-filled conditions.

• Convergence Security Journal
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• v.19 no.1
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• pp.67-78
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• 2019

Most existing facial expression recognition methods use a uniform grid method that divides the entire facial image into uniform blocks when describing facial features. The problem of this method may include non-face backgrounds, which interferes with discrimination of facial expressions, and the feature of a face included in each block may vary depending on the position, size, and orientation of the face in the input image. In this paper, we propose a variable-size block method which determines the size and position of a block that best represents meaningful facial expression change. As a part of the effort, we propose the way to determine the optimal number, position and size of each block based on the facial feature points. For the evaluation of the proposed method, we generate the facial feature vectors using LDTP and construct a facial expression recognition system based on SVM. Experimental results show that the proposed method is superior to conventional uniform grid based method. Especially, it shows that the proposed method can adapt to the change of the input environment more effectively by showing relatively better performance than exiting methods in the images with large shape and orientation changes.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.237-245
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• 2003

Since the velocity is dependent on the fiber orientation in anisotropic composites, the application of traditional acoustic emission (AE) source location techniques based on the constant velocity to composite structures has been practically impossible. The anisotropy makes the source location procedure complicated and deteriorates the accuracy of the location. In this study, we have divided the region of interest(ROI) into a set of finite elements, taken each element as a virtual source, and calculated the arrival time differences between sensors by using the velocities at every degree from 0 to 90. The calculated and the experimentally measured values of the arrival time difference aye then compared to minimize the location error. The results from two different materials, namely AA6061-T6 and CFRP(uni-directional; UD, $[0]_{32}4$) laminate confirmed the practical usefulness of the proposed method.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.1012-1018
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• 2007

본 논문에서는 비전 기반 3차원 얼굴 모델의 자동 표정 생성 시스템을 제안한다. 기존의 3차원 얼굴 애니메이션에 관한 연구는 얼굴의 움직임을 나타내는 모션 추정을 배제한 얼굴 표정 생성에 초점을 맞추고 있으며 얼굴 모션 추정과 표정 제어에 관한 연구는 독립적으로 이루어지고 있다. 제안하는 얼굴 모델의 표정 생성 시스템은 크게 얼굴 검출, 얼굴 모션 추정, 표정 제어로 구성되어 있다. 얼굴 검출 방법으로는 얼굴 후보 영역 검출과 얼굴 영역 검출 과정으로 구성된다. HT 컬러 모델을 이용하며 얼굴의 후보 영역을 검출하며 얼굴 후보 영역으로부터 PCA 변환과 템플릿 매칭을 통해 얼굴 영역을 검출하게 된다. 검출된 얼굴 영역으로부터 얼굴 모션 추정과 얼굴 표정 제어를 수행한다. 3차원 실린더 모델의 투영과 LK 알고리즘을 이용하여 얼굴의 모션을 추정하며 추정된 결과를 3차원 얼굴 모델에 적용한다. 또한 영상 보정을 통해 강인한 모션 추정을 할 수 있다. 얼굴 모델의 표정을 생성하기 위해 특징점 기반의 얼굴 모델 표정 생성 방법을 적용하며 12개의 얼굴 특징점으로부터 얼굴 모델의 표정을 생성한다. 얼굴의 구조적 정보와 템플릿 매칭을 이용하여 눈썹, 눈, 입 주위의 얼굴 특징점을 검출하며 LK 알고리즘을 이용하여 특징점을 추적(Tracking)한다. 추적된 특징점의 위치는 얼굴의 모션 정보와 표정 정보의 조합으로 이루어져있기 때문에 기하학적 변환을 이용하여 얼굴의 방향이 정면이었을 경우의 특징점의 변위인 애니메이션 매개변수를 획득한다. 애니메이션 매개변수로부터 얼굴 모델의 제어점을 이동시키며 주위의 정점들은 RBF 보간법을 통해 변형한다. 변형된 얼굴 모델로부터 얼굴 표정을 생성하며 모션 추정 결과를 모델에 적용함으로써 얼굴 모션 정보가 결합된 3차원 얼굴 모델의 표정을 생성한다.

• Proceedings of the KIEE Conference
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• summer
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• pp.21-23
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• 2004

전력 에너지는 안정하고 신뢰할 수 있도록 고장에 대한 빠른 대처가 필요하다. 고장시 빠른 수리를 위해서는 보수 승무원에게 고장 위치를 정확하게 알려주어 올바른 위치에 도착할 수 있도록 고장점 표정 알고리즘의 정확도가 요구된다. 본 논문에서는 기존 1회선 분기점을 갖는 병행 2회선 송전선로의 고장점 표정 알고리즘을 이용하여 정확한 고장 위치를 찾는 방법으로 개선된 NVP(N-version programming) 모델을 적용한 새로운 계산 방법을 제안한다. 송전선로의 고장 데이터는 EMTP(Electro Magnetic Transients Program)을 사용하여 154[kV], 25[km] 분기된, 병행 2회선 송전선로에서 고장지진과 고장저항의 데이터존 이용하여 시뮬레이션했다.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.375-384
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• 2011

This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.205-211
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• 2003

Acoustic emission (AE) technique has been applied to not only mechanical property testing but also on-line monitoring of the el)tire structure or a limit zone only. Although several AE devices have already been developed for the on-line monitoring, the price of these systems is very high and it is difficult for the field to apply yet. In this study, wc developed a specially designed PC-based source location system using the A/D board. The source location technique is very important to identify the source, such as crack, leak detection. However, since the AE waveforms obtained from transducers are very difficult to distinguish the defect signals, therefore, it is necessary to consider the signal analyses of the transient waveform. Wavelet Transform (WT) is a powerful tool for processing transient signals with temporally varying spectra that helps to resolve high and low frequency transients components effectively In this study, the analyses of the AE signals are presented by employing the WT analyses. AE results are compared the PC-based source location system using A/D board with the commercial AE system.