• 한국정밀공학회지
• /
• 제15권6호
• /
• pp.167-174
• /
• 1998

The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2004년도 추계학술대회 논문집
• /
• pp.426-429
• /
• 2004

To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.

• 한국측량학회지
• /
• 제28권3호
• /
• pp.361-367
• /
• 2010

이 연구에서는 국토지리정보원 14개 GPS 상시관측소에서 수집된 약 5년간의 GPS 자료를 고정밀 처리하여 연속적인 수직좌표 시계열을 생성하였다. 그리고 1차 선형회귀식을 사용하여 GPS 상시관측소 속도를 계산하였으며, GPS 수직좌표 변동 경향을 분석하기 위해 주성분분석을 실시하였다. 가장 우세한 성분의 신호를 나타내는 모드 1을 대상으로 분석한 결과 약 4.2mm/yr의 수직 속도가 산출되었다. 그리고 모드 1의 고유 벡터 값에서 일관성을 보였다. 따라서 분석대상 기간 동안에는 모든 관측소가 일제히 상승하는 신호를 보이고 있음을 알 수 있었다. 또한 14개 GPS 상시관측소 시계열에서 주성분분석을 통해 산출된 모드 1 신호를 제거하고 모드 1의 신호 제거 전 후에 따른 관측소 수직좌표 시계열의 정밀도 변화를 분석하였다. 그 결과, 수직좌표 시계열의 정밀도는 평균 34.8% 향상되었다.

• 한국정밀공학회지
• /
• 제15권12호
• /
• pp.226-235
• /
• 1998

This study proposes the analysis and evaluation of method of time series of ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. The features are extracted from time series data for analysis of weld defects quantitatively. For this purpose, analysis objectives in this study are fractal dimension, Lyapunov exponent, and strange attractor on hyperspace. The Lyapunov exponent is a measure of rate in which phase space diverges nearby trajectories. Chaotic trajectories have at least one positive Lyapunov exponent, and the fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal(correlation) dimensions and Lyapunov exponents show the mean value of 4.663, and 0.093 relatively in case of learning, while the mean value of 4.926, and 0.090 in case of testing in slag inclusion(weld defects) are shown. Therefore, the proposed chaotic feature extraction can be enhancement of precision rate for ultrasonic pattern recognition in defecting signals of weld zone, such as slag inclusion.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1996년도 추계학술대회 논문집
• /
• pp.406-412
• /
• 1996

Optimal trajectory for a robot manipulator minimizing actuator torques or energy consumption in a fixed traveling time is obtained in the presence of obstacles. All joint displacements are represented in finite terms of Fourier cosine series and the coefficients of the series are obtained optimally by nonlinear programming. Thus, the geometric path need not be prespecified and the full dynamic model is employed. To avoid the obstacles, the concept of penalty area is newly introduced and this penalty area is included in the performance index with an appropriate weighting coefficient. This optimal trajectory will be useful as a geometric path in the minimum-time trajectory planning problem.

• 한국지반환경공학회 논문집
• /
• 제16권3호
• /
• pp.15-21
• /
• 2015

2007년 <지반조사 성과 전산화 및 활용에 관한 지침>에 따라 국토지반정보 통합DB센터화 사업이 추진되어 건설현장에 생성되는 지반정보와 관련된 각종 조사, 정보의 효율적인 수집 및 활용을 위하여 시추정보 유통프로세스 사업이 진행되고 있다. 국토지반정보 통합DB센터에 따르면 2014년 6월을 기준으로 약 18만공의 지반정보가 정리되어 있으며 현재에도 지반정보에 대한 데이터베이스 구축이 활발하게 진행되고 있다. 본 연구는 이러한 지반정보 유통프로세스 사업이 시추정보 정밀도에 미치는 영향을 살펴보기 위하여 현장에서 가장 많이 활용되고 있는 지하수위와 지층심도에 관한 시추정보를 이용하여 정밀도 시계열 분석을 실시하였다. 정밀도 분석은 정규분포와 첨도를 통한 통계학적 방법을 이용하였다. 결과적으로 유통프로세스 사업이 시추정보 정밀도 향상에 긍정적인 영향을 미치는 것을 확인할 수 있었으며 보다 많은 정보를 바탕으로 다양한 시추정보의 정밀도 검증을 수행할 경우 각 지역에 따른 시추정보 정밀도 평가도 수행할 수 있을 것으로 기대된다.

• 한국정밀공학회지
• /
• 제15권1호
• /
• pp.137-144
• /
• 1998

For a model system consisted of four pneumatic cylinders with strokes of 10, 20, 40 and 80 mm, investigation was carried out experimentally and numerically about the reliability of system with elastic and viscous load. The elastic load affects the performance of each cylinder in cylinder series, and changes the time lag and the velocity of the piston which makes the positioning control rather difficult. Taking the effects of the elastic load into consideration, positioning can be carried out comparatively smoothly by only adjusting the driving timing. The effect of a viscous load reduces the vibration of each moving body in the cylinder series and also reduces the over-travelled distance which happens when several cylinders move at the same time. For reasons, a positioning with a viscous load can be relatively smoothly carried out even without the timing control.

• 한국정밀공학회지
• /
• 제10권4호
• /
• pp.94-103
• /
• 1993

In this work, the imaginary part of the inner modulation transfer function of the cutting dynamics is introduced for tool wear monitoring. Time-series method is utilized to construct the general three dimensional cutting dynamics whose imaginary part of the inner modulation transfer funcition shows the proportionality to tool wear at the natural frequency of the machine tool dynamics. Thus model is reduced to single-input single-output model without altering the proportionality characteristics to tool wear and implemented to the dual computer system in which one computer performs measurement while the other calculates the imaginary part of the inner modulation transfer function of the cutting dynamics by the batch least square method. The values of the imaginary part at the natural requency of the machine tool structure in the cutting direction are compared to the one calculated during machining with a brand new tool to decide the current status of the tool. The experiments shows the relevance of the proposed concept.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2007년도 춘계학술대회 논문집
• /
• pp.709-710
• /
• 2007

• 한국시뮬레이션학회논문지
• /
• 제5권1호
• /
• pp.1-12
• /
• 1996

We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.