• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.2
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• pp.119-127
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• 2004

Butterfly valves are popularly used in service in the industrial and water works pipeline systems with large diameter because of its lightweight, simple structure and the rapidity of its manipulation. Sometimes cavitation can occur. resulting in noise, vibration and rapid deterioration of the valve trim, and do not allow further operation. Thus, the monitoring of cavitation is of economic interest and is very importance in industry. This paper proposes a condition monitoring scheme using statistical feature evaluation and support vector machine (SVM) to detect the cavitation conditions of butterfly valve which used as a flow control valve at the pumping stations. The stationary features of vibration signals are extracted from statistical moments. The SVMs are trained, and then classify normal and cavitation conditions of control valves. The SVMs with the reorganized feature vectors can distinguish the class of the untrained and untested data. The classification validity of this method is examined by various signals that are acquired from butterfly valves in the pumping stations and compared the classification success rate with those of self-organizing feature map neural network.

• Coupled systems mechanics
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• v.12 no.1
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• pp.1-20
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• 2023

On the basis of the explicit time-domain method, an investigation is performed on the influence of the rotational stiffness and rotational damping of the vehicle body and front-rear bogies on the dynamic responses of the vehicle-bridge coupled systems. The equation of motion for the vehicle subsystem is derived employing rigid dynamical theories without considering the rotational stiffness and rotational damping of the vehicle body, as well as the front-rear bogies. The explicit expressions for the dynamic responses of the vehicle and bridge subsystems to contact forces are generated utilizing the explicit time-domain method. Due to the compact wheel-rail model, which reflects the compatibility requirement of the two subsystems, the explicit expression of the evolutionary statistical moment for the contact forces may be performed with relative ease. Then, the evolutionary statistical moments for the respective responses of the two subsystems can be determined. The numerical results indicate that the simplification of vehicle model has little effect on the responses of the bridge subsystem and the vehicle body, except for the responses of the rotational degrees of freedom for the vehicle subsystem, regardless of whether deterministic or random analyses are performed.

• Journal of the Korean Society of Groundwater Environment
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• v.2 no.1
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• pp.9-13
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• 1995

In the stream-aquifer setting, this study evaluated the effects of spatial variability in nonpoint sources and hydraulic conductivity on groundwater outflow concentration history. Monte Carlo experiments based on the advection-dispersion equation were used to determine the statistical moments of groundwater outflow concentration history. The comparison between a spatially distributed model and spatially integrated model (SID) was made in order to examine the possibility of applying SID to the problems of nonpoint source groundwater pollution.

• Journal of the Society of Naval Architects of Korea
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• v.32 no.1
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• pp.37-41
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• 1995

In order to analyze the rolling motion of a ship in random beam waves we use the partial stochastic linearization method. The quadratic damping and the nonlinear restoring moments given by the odd polynomials up to the 11th order are added to a single degree of freedom linear equation of roll motion. The irregular excitation moment is assumed to be the Gaussian white noise. The statistical characteristics of the response by the partial stochastic linearization method is compared with results by the equivalent linearization method and Monte Carlo simulation. It is fecund that the partial stochastic linearization method is not necessarily superior to the equivalent linearization method.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.205-220
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• 2009

For modeling skewed semicircular data, we derive new family of the exponential distributions. We extend it to the l-axial exponential distribution by a transformation for modeling any arc of arbitrary length. It is straightforward to generate samples from the f-axial exponential distribution. Asymptotic result reveals two things. The first is that linear exponential distribution can be used to approximate the l-axial exponential distribution. The second is that the l-axial exponential distribution has the asymptotic memoryless property though it doesn't have strict memoryless property. Some trigonometric moments are also derived in closed forms. Maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for goodness of fit test of the l-axial exponential distribution. We finally obtain a bivariate version of two kinds of the l-axial exponential distributions.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1125-1145
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• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• ETRI Journal
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• v.32 no.5
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• pp.687-694
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• 2010

Breaks in presence (BIP) are those moments during virtual environment (VE) exposure in which participants become aware of their real world setting and their sense of presence in the VE becomes disrupted. In this study, we investigate participants' experience when they encounter technical anomalies during game play. We induced four technical anomalies and compared the BIP responses of a navigation mode game to that of a combat mode game. In our analysis, we applied a linear mixed model (LMM) and compared the results with those of a conventional regression model. Results indicate that participants felt varied levels of impact and recovery when experiencing the various technical anomalies. The impact of BIPs was clearly affected by the game mode, whereas recovery appears to be independent of game mode. The results obtained using the LMM did not differ significantly from those obtained using the general regression model; however, it was shown that treatment effects could be improved by consideration of random effects in the regression model.

• Structural Engineering and Mechanics
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• v.6 no.5
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• pp.473-484
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• 1998

The first and second moments of response variables for SDOF systems with hysteretic nonlinearity are obtained by a direct linearization procedure. This adaptation in the implementation of well-known statistical linearization methods, provides concise, model-independent linearization coefficients that are well-suited for numerical solution. The method may be applied to systems which incorporate any hysteresis model governed by a differential constitutive equation, and may be used for zero or non-zero mean random vibration. The implementation eliminates the effort of analytically deriving specific linearization coefficients for new hysteresis models. In doing so, the procedure of stochastic analysis is made independent from the task of physical modeling of hysteretic systems. In this study, systems with three different hysteresis models are analyzed under various zero and non-zero mean Gaussian White noise inputs. Results are shown to be in agreement with previous linearization studies and Monte Carlo Simulation.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1345-1353
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• 2009

We introduce a simple methodology, so-called generalized gamma-polynomial approximation, based on moment-matching technique to approximate survival and hazard functions in the context of parametric survival analysis. We use the generalized gamma-polynomial approximation to approximate the density and distribution functions of convolutions and finite mixtures of random variables, from which the approximated survival and hazard functions are obtained. This technique provides very accurate approximation to the target functions, in addition to their being computationally efficient and easy to implement. In addition, the generalized gamma-polynomial approximations are very stable in middle range of the target distributions, whereas saddlepoint approximations are often unstable in a neighborhood of the mean.

• ETRI Journal
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• v.17 no.3
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• pp.45-63
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• 1995

This paper proposes an algorithm to improve the correlation between giga-hertz transverse electromagnetic (GTEM) cell and open area test site (OATS). It is based on the dipole modeling process of an unknown source object in a GTEM cell and on the evaluation of the approximate far field equations correlated with measured GTEM powers at output port of the GTEM cell. In this algorithm, the relative phase differences between dipole moments play an important part in modeling the test object as a set of dipoles and offer stable calculation of emission values. The radiated emission test using this algorithm requires fifteen orientations of equipment under test, but the increased orientations as compared with the previous method have little effect on the time needed for testing. Radiation from a notebook computer has been tested for statistical analysis of the correlation between GTEM data and OATS data. The emission test results of the notebook computer show that the mean, the standard deviation, and the correlation coefficient are -0.62, 1.99, and +0.85, respectively. These figures indicate that this algorithm provides improved accuracy in the measurement of electromagnetic emissions over the previous method.