• Title/Summary/Keyword: Precision time-series

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Ultrasonic Pattern Recognition of Welding Defects Using the Chaotic Feature Extraction (카오스 특징 추출에 의한 용접 결함의 초음파 형상 인식)

  • Lee, Won;Yoon, In-Sik;Lee, Byung-Chae
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.6
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    • pp.167-174
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    • 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.

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Research for 3-D Information Reconstruction by Appling Composition Focus Measure Function to Time-series Image (복합초점함수의 시간열 영상적용을 통한 3 차원정보복원에 관한 연구)

  • 김정길;한영준;한헌수
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.426-429
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    • 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.

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Principal Component Analysis of GPS Height Time Series from 14 Permanent GPS Stations Operated by National Geographic Information Institute (주성분분석을 통한 국토지리정보원 14개 GPS 상시관측소 수직좌표 시계열 분석)

  • Kim, Kyeong-Hui;Park, Kwan-Dong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.3
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    • pp.361-367
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    • 2010
  • We produced continuous vertical time series of 14 permanent GPS stations operated by National Geographic Information Institute by processing about five years of data. Then we computed the height velocities by using a linear regression fitting of those time series, and did principal component analysis to understand the overall characteristics of the series. The prominent signal obtained as the first mode of PCA results showed an average of 4.2 mm/yr vertical velocity. The values of the first mode eigenvectors were consistent at all sites. Thus, we concluded that all the 14 stations are uplifting nearly at the same velocity for the test period. Then changes of precision before and after removing the first mode signal from the 14 height time series were analyzed. As a result, the precision improved 34.8% on average.

Chaotic Evaluation of Slag Inclusion Welding Defect Time Series Signals Considering the Hyperspace (초공간을 고려한 슬래그 혼입 용접 결함 시계열 신호의 카오스성 평가)

  • Yi, Won;Yun, In-Sik
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.12
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    • pp.226-235
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    • 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.

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Optimal Motions for a Robot Manipulator amid Obstacles by the Representation of Fourier Series (후리에 급수 표현에 의한 로봇 팔의 장애물 중에서의 최적 운동)

  • 박종근
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.406-412
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    • 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.

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Time-series Analysis of Precision the Domestic Boring Investigation Data (국내 시추조사 자료 정밀도 시계열 분석)

  • Jang, Yonggu;Kim, Youngsun;Chae, Deokho;Cho, Wanjei
    • Journal of the Korean GEO-environmental Society
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    • v.16 no.3
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    • pp.15-21
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    • 2015
  • Since the introduction of 'the rule for computerizing subsoil investigation results and its application' in 2007, the DB construction of the national geotechnical information by Ministry of Land, Transport and Maritime Affairs (MOLTMA) has been performed. According to the Integrated DB Center of National Geotechnical Information, there have been 180 thousands borehole information stored in the system. In this study, the time-series analyses of precision on the most used information, the depth of stratum and ground water level, were performed to evaluate the effect of the initiation of the rule established in 2007. The precisions were evaluated based on the statistical analyses using kurtosis and normal distribution. Based on the results, the increase of precision after 2007 and the affirmative effects of the rule established in 2007 are confirmed. Furthermore, the precision of the regional information can be achieved with the precision analyses on the information from various areas.

Digital Positioning Control of Pneumatic Cylinder System with Elastic and Viscous Load (탄성 및 점성 부하시 공기압 실린더 시스템의 디지털 위치 제어)

  • 박명관;문영진;편창관
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.1
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    • pp.137-144
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    • 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.

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Tool Wear Monitoring Scheme by Modeling of the Cutting Dynamics by Time-series Method (Time-series 방법으로 모델링한 절삭역학에 의한 공구마모감시방법)

  • Kwon, Won-Tae
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.4
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    • pp.94-103
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    • 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.

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A Neural Network-Driven Decision Tree Classifier Approach to Time Series Identification (인공신경망 기초 의사결정트리 분류기에 의한 시계열모형화에 관한 연구)

  • 오상봉
    • Journal of the Korea Society for Simulation
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    • v.5 no.1
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    • pp.1-12
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    • 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.

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