• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.9 no.2
• /
• pp.45-51
• /
• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Journal of Welding and Joining
• /
• v.16 no.6
• /
• pp.86-96
• /
• 1998

This study proposes the analysis method of time series ultrasonic signal using the chaotic feature extraction for degradation extent evaluation. Features extracted from time series data using the chaotic time series signal analyze quantitatively degradation extent. For this purpose, analysis objective in this study is fractal dimension, lyapunov exponent, strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal correlation) dimensions, lyapunov exponents, energy variation showed values of 2.217∼2.411, 0.097∼ 0.146, 1.601∼1.476 voltage according to degardation extent. The proposed chaotic feature extraction in this study can enhances precision ate of degradation extent evaluation from degradation extent results of the degraded materials (SA508 CL.3)

• Journal of Korean Society of Rural Planning
• /
• v.16 no.3
• /
• pp.11-17
• /
• 2010

With international attention to the rural landscape, there have been landscape management and conservation efforts. Because it contains characteristics of rural area, rural landscape has been recognized as an important component of rurality. With rural amenity resources survey projects launched since 2005, rural landscape categorization and evaluation such as resource value, use value, beauty, originality, traditionality, maintenance are performed by expert questionnaire survey and 100 rural amenity resources are selected. In this study, we performed fractal analysis for developing evaluation system of the rural landscape photographs. In evaluating processes, main and surrounding landscape are separated and fractal indexes are calculated and analyzed with beauty value scoured by experts. Results show that beauty value is not significantly related with fractal index but differences of main and surrounding landscape fractal index.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.161-164
• /
• 1995

Nonlinear analysis of various phenomena has been developed with improvement of computer. The characteristics form nonlinear analysis are available in monitoring and diagnosis state of system. There are many nonlinear property in cutting process, but nonlinear signals have been considered as noise. In this study, nonlinear analysis technique is applied and it will be verified that cutting force is chaos by calculating Lyapunov exponents,fractal dimension and embedding dimension. The relation between characteristic parameter calculated form sensor signal and various cutting condition is investigated.

• Journal of the Korean association of regional geographers
• /
• v.9 no.4
• /
• pp.481-492
• /
• 2003

This study aims to analyze quantitatively changes of forest and cropland landscape due to cropland increase toward higher mountain slope during 9 years from 1993 to 2002, using Landsat images and field survey in the vicinity of Manpo and Gangae cities, Jagang Province, Northwest Korea, During 9 years, cropland has increased as 49.9%, forest area decreased as 16%. The spatial characteristics of cropland changes present that average elevation of cropland are increased from 381m of 1993 year to 412m of 2002 year, and average gradient increased from $10^{\circ}$ to $13^{\circ}$. In increased area of cropland during 9 years, the average elevation is 455m, and average gradient is $15^{\circ}$ with maximum gradient $70^{\circ}$. Analysis of the patch phenomena by fragmentation of vegetation landscape show that number of patch increased from 394 to 1,241 and also values of shape index, and fractal dimension of vegetation are increased slightly, during 9 years. Croplands have developed mainly in mountain slopes of elevation between 450 to 750m. For improvement of agricultural productivity, it should be required political and social stabilization, international and South Korea's assistance, and restoration of mountain forest.

• Journal of the Korean Society of Radiology
• /
• v.7 no.1
• /
• pp.25-30
• /
• 2013

In this work, we investigate the statistical properties of gamma exposure rates using well-known analysis methods, such as Autocorrelation Function Analysis(ACF), Rescaled Range Analysis(R/S Analysis), and Detrended Fluctuation Analysis(DFA). Especially, DFA is an important method to reliably detect long-range correlations in non-stationary time series. Our data are measured by Gangneung regional radiation monitoring station over the period of 1998 to 2011. First, we find a crossover indicating two different governing regimes in fluctuations of gamma exposure rates. Within a year, they show a strong long-ranged memory while this property vanishes over the range of time period longer than one year. Second, our finding is very securely supported by a variety of analysis tools. Those tools yield many relevant exponents which satisfies the well known relation between them.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.12
• /
• 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.

• Journal of Welding and Joining
• /
• v.16 no.5
• /
• pp.108-118
• /
• 1998

This study proposes th analysis and evaluation method of time series ultrasonic signal using the chaos feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaos time series signal analyze quantitatively weld defects. For this purpose, analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaosity resulting from distance shifts such as 0.5 and 1.0 skip distance. Such differences in chaosity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos feature extraction, feature values of 4.511 and 0.091 in the case of side hole and 4.539 and 0.115 in the case of vertical hole were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaos feature extraction in this study can enhances ultrasonic pattern recognition results from defect signals of weld zone such as side hole and vertical hole.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.23 no.7 s.166
• /
• pp.1065-1074
• /
• 1999

This study proposes the analysis and evaluation method of time series ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaotic time series signal analysis quantitatively welding defects. For this purpose analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaoticity resulting from distance shills such as 0.5 and 1.0 skip distance. Such differences in chaoticity enables the evaluation of unique features of defects in the weld zone. In experiment fractal(correlation) dimension and Lyapunov exponent extracted from 6dB ultrasonic defect signals of weld zone showed chaoticity. In quantitative chaotic feature extraction, feature values(mean values) of 4.2690 and 0.0907 in the case of porosity and 4.2432 and 0.0888 in the case of incomplete penetration were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaotic feature extraction in this study enhances ultrasonic pattern recognition results from defect signals of weld zone such as vertical hole.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2005.10a
• /
• pp.387-392
• /
• 2005

The research was performed to predict the potential landslide with roughness index. It was known that fractal dimension and surface area index can be represented the topography, specially when the natural slopes were rough or rugged. A test site was selected and fractal dimension and surface area index were calculated from the irregular triangle network. Fractal dimension were ranged between $2.016{\sim}2.046$ and surface area index $1.56E+07{\sim}2.59E+07$. Surface area index increased as fractal dimension increased. Slope stability was calculated by infinite slope stability analysis model and was compared to slope stability by fractal and surface area index. In the result, unsafe zones where slope stability is under 1.1 were $5.11{\sim}6.25%$ for the test site. It can be said that fractal dimension and surface area index are a good index to evaluate the slope stability because when fractal dimension and surface area index are greater, then stability of the site is more unsafe.