• Journal of Navigation and Port Research
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• v.26 no.3
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• pp.281-288
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• 2002

It might be true that both experimental and analytic techniques have been developed in the vibration analysis end engineering. It could not be said, however, that the experimental method has been also developed as much as analytic method, such as Finite Element Method One of the reason is that computation time becomes longer and that the solution often diverges depending on the choice of initial value in solving nonlinear equation. The equation in experimental modal analysis is usually composed of the nonlinear term of natural frequency and modal damping ratio, and the linear one of equivalent stiffness. In this study, the nonlinear terms were solved first, and then the linear term was obtained. The experimental modal parameters were estimated, applying the developed experimental modal analysis curve-fitting method to the super-structure model. In addition, the number of modes and modal damping ratio could be easily determined by the developed program with the application of graphical techniques and with easy handling button.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1601-1606
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• 1991

We present an algorithm to approximate the Voronoi diagrams of 2D objects bounded by algebraic curves. Since the bisector curve for two algebraic curves of degree d can have a very high algebraic degree of 2 * d$^{4}$, it is very difficult to compute the exact algebraic curve equation of Voronoi edge. Thus, we suggest a simple polygonal approximation method. We first approximate each object by a simple polygon and compute a simplified polygonal Voronoi diagram for the approximating polygons. Finally, we approximate each monotone polygonal chain of Voronoi edges with Bezier cubic curve segments using least-square curve fitting.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.96-107
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• 1997

The recent stream to reliability prediction is that it is totally inclusive in depth to consider even the operating and environmental condition at the level of finished goods as well as component itselves. In this study, firstly we present the reliability prediction methods by entire failure rate model which failure rate at the system level is added to the failure rate model at the component level. Secondly we build up the improved bases of reliability demonstration through a, pp.ication of Kaplan-Meier, Cumulative hazard, Johnson's methods as non-parametric and Maximum Likelihood Estimator under exponential & Weibull distribution as parametric. And also present the methods of curve fitting to piecewise failure rate under Weibull distribution, PRST (Probability Ratio Sequential Test), curve fitting to S-shaped reliability growth curve, computer programs of each methods. Lastly we show the practical for determination of optimal burn-in time as a method of reliability enhancement, and also verify the practical usefulness of the above study through the a, pp.ication of failure and test data during 1 year.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.913-917
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• 2013

During the restoration process of primary restorative transmission system, some over voltages may happen due to nonlinear interaction between unloaded transformers and transmission systems. These over voltages caused by harmonic resonance can be suppressed by inserting damping loads before energizing transformers. But it is very difficult to predict the occurrence possibility of harmonic resonance and complex simulation must be repeated to estimate the sufficient damping loads. This paper presents a damping loads prediction system to prevent harmonic resonance. Detailed analysis of the relationship between harmonic resonance and the amount of damping loads is discussed. The prediction system is developed using a curve fitting and a neural network based on this relationship. A curve fitting used a Gaussian function based on non-linear least square method and multi-layer back-propagation neural network is applied. The system is applied to primary restorative transmission lines in korean power system and the result showed satisfactory performance.

• Journal of Sensor Science and Technology
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• v.9 no.6
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• pp.440-447
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• 2000

This paper describes a practical system to classify material temperature responses by composition of curve fitting and neuro-fuzzy inference. There are problems with a classification system which utilizes temperature responses. It requires too much time to approach the steady state of temperature response and it has to be filtered to remove the noise which occurs in experiments. Thus, this paper proposes a practical method using curve fitting only for transient state to remove the above problems of time and noise. Using the neuro-fuzzy system, the thermal conductivity of the material can be inferred on various ambient temperatures. So the material can be classified via its inferred thermal conductivity. To realize the system, we designed a contact sensor which has a similar structure with human finger, implemented a hardware system, and developed a classification software of curve fitting and neuro-fuzzy algorithm.

• Current Optics and Photonics
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• v.7 no.6
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• pp.701-707
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• 2023

In laser imaging, accurate extraction of the laser's center is essential. Several methods exist to extract the laser's center in an image, such as the geometric mean, the parabolic curve fitting, and the Gaussian curve fitting, etc. The Gaussian curve fitting is the most suitable because it is based on the physical properties of the laser. The width of the Gaussian laser beam depends on the distance from the laser source to the target object. It is assumed in general that the distance remains constant at a laser spot resulting in a symmetric Gaussian model for the laser image. However, on a curved surface of the object, the distance is not constant; The laser beam is narrower on the side closer to the focal point of the laser light and wider on the side closer to the laser source, which causes the distribution of the laser beam to skew. This study presents a modified Gaussian model in the laser imaging to incorporate the slant angle of a curved object. The proposed method is verified with simulation and experiments.

• Geomechanics and Engineering
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• v.23 no.5
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• pp.431-439
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• 2020

Soil-water retention curve (SWRC) contains key information for the application of unsaturated soil mechanics principles to engineering practice. The SWRC variables are commonly used to describe the hydro-mechanics of soils. Generally, these parameters are determined using the graphical method which can be time consuming. The SWRC is highly dependent on the pore size distribution (PSD). Theoretically, the PSD obtained by mercury intrusion porosimetry test can be used to determine some SWRC variables. Moreover, the relationship between SWRC and shrinkage curve has been investigated. A new method to determine total SWRC variables directly without curve-fitting procedure is proposed. Substituting the variables into linear SWRC equations construct SWRC. A good agreement was obtained between predicted and measured SWRCs, indicating the validity of the proposed method for unimodal SWRC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.33-39
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• 2018

An additive noise reduction algorithm for a mass spectrum analyzer is proposed. From the measured ion signal, we first used an estimated threshold from the mode of the measured signal to eliminate background noises with the white Gaussian characteristics. Also, a signal block corresponding to each mass index is constructed to perform a second order curve fitting and a linear approximation to signal block. In this process, the effective signal block composed of only the ion signal can be reconstructed by removing the impulsive noises and the sample signals which are insufficient to be viewed as normal ion signals. By performing curve fitting on the effective signal block, the noise-free mass spectrum can be obtained. To evaluate the performance of the proposed method, a simulation was performed using the signals acquired from the development equipment. Simulation results show the validity of the threshold setting from the mode and the superiority of the proposed curve fitting and linear approximation based noise canceling algorithm.

• Journal of Welding and Joining
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• v.10 no.4
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• pp.190-198
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• 1992

Among the variety of welding processes available, the flux cored arc welding is one of the most frequently used process, because of its wide range of application and high productivity. The weld joint tracking is indispensable to improve the flexibility of the arc welding robot application for the flux cored arc welding (FCAW) process. In this study, an arc sensor which utilizes the electrical signal obtained from the welding arc itself was developed for weld joint tracking in FCAW. Because a model of the welding arc in flux cored arc welding was required to develop the arc sensor, a mathematical model was proposed by analysing the welding arc behaviour, and also an experimental model by using the factorial experiment and least square method. For overcoming the fluctuation in the welding current signal during tracking the weld joint, it was fitted to a curve which is inversely proportional to a trace of tip-to-workpiece distance by using the quadratic curve-fitting method.

• Journal of Power System Engineering
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• v.21 no.6
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• pp.86-93
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• 2017

Silicone rubber wire seals are widely used in automotive connector systems for waterproofing and so on. The purpose of this paper is to predict and evaluate the sealing performance of wire seals using finite element analysis. The material properties of the rubber seals were determined by the curve fitting of uniaxial tensile test and equibiaxial tensile test data. The response surface method was used to determine the optimum shape of the wire seal. In order to verify the accuracy and reliability of the simulations on the deformation prediction of wire seals, experiments were also carried out.