• Proceedings of the KSME Conference
• /
• 2001.11a
• /
• pp.791-796
• /
• 2001

Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time evaluation of the welding quality is very important in enhancing the efficiency of welding. In this study, the plasma and molten metal which are generated during laser welding were measured using the UV sensor and IR sensor. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, focus off, and nozzle change. Also, a system was formulated which uses the measured signals with a fuzzy pattern recognition method which is used to perform real-time evaluation of the welding quality and the defects which can occur in laser welding. Weld quality prediction program was developed using previous weld results and statistical program which could show the trend of weld quality and signal was developed.

• Journal of Advanced Marine Engineering and Technology
• /
• v.14 no.1
• /
• pp.62-71
• /
• 1990

Two-dimensional turbulent wake flow past a rectangular cylinder is investigated experimentally by using the linearized constant temperature hot-wire anemometer. Some of turbulent characteristics are obtained at the range of X=6B-500B downstream from the cylinder and the Reynolds number range is 500-2800. For the statistical treatment, autocorrelation coefficient, probability density function and power spectral density function are obtained by using the signal analyzer. It is clear that coherent structure of strong periodic eddies exists to the position of 20B downstream from the cylinder, and its feature is similar to round type as nearer to the cylinder while it is stretched longitudinally along with flow direction as the distance from the cylinder is increased to downstream.

• Journal of Korean Society for Quality Management
• /
• v.34 no.2
• /
• pp.122-128
• /
• 2006

One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.9
• /
• pp.109-117
• /
• 1997

A new relaxation algorithm based on distribution of matched errors and possibility is proposed to solve efficiently correspondence problem. This algorithm can be applied to various method, such as BMA, feature-, and region-based matching methods, by modifying its smoothness function. It consists of two stages which are transformation and iteration process. In transformation stage, the errors obtained by any matching algorithm are transformed to possibility values according to these statistical distribution. Each grade of possility is updated by some constraints which are defined as smoothness, uniqueness, and discontinuity factor in iteration stage. The discontinuity factor is used to reserve discontinuity of disparity. In conventional methods, it is difficult to find proper weights and stop condition, because only two factors, smoothness and uniqueness, have been used. However, in the proposed mthod, the more smoothing is not ocurred because of discontinuity factor. And it is efective to the various image, even if the image has a severe noise and repeating patterns. In addition, it is shown that the convergence rate and the quality of output are improved.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2008.05a
• /
• pp.293-296
• /
• 2008

Contract power conversion factor which is applied to estimate contract power of general customers IS an important standard to caculate transformer capacity. This paper shows a reasonable contract power conversion factor, that was made by the systematic and statistical way considering actual conditions, such as investigated contract power and peak power for the last 5 years of each customer for 132 office building customers as to AMR system. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and thus it was carried the linear and nonlinear regression analysis. Therefore, this paper compared characteristics for a contract power conversion factor which is applied to calculate contract power with characteristics for a regression model for customers which maximum utilization factor of transformer is more than 60%.

• Journal of Multimedia Information System
• /
• v.3 no.2
• /
• pp.1-8
• /
• 2016

In this paper, we propose a method to automatically diagnose various diseases. The input data consists of electrocardiograph (ECG) recordings. We extract R-to-R interval (RRI) signals from ECG recordings, which are preprocessed to remove trends and ectopic beats, and to keep the signal stationary. After that, we perform some prospective analysis to extract time-domain parameters, frequency-domain parameters, and nonlinear parameters of the signal. Those parameters are unique for each disease and can be used as the statistical symptoms for each disease. Then, we perform feature selection to improve the performance of the diagnosis classifier. We utilize the selected features to diagnose various diseases using machine learning. We subsequently measure the performance of the machine learning classifier to make sure that it will not misdiagnose the diseases. The first two steps, which are R-to-R extraction and preprocessing, have been successfully implemented with satisfactory results.

• Journal of Mechanical Science and Technology
• /
• v.20 no.3
• /
• pp.391-398
• /
• 2006

This work involves a method for modeling the flow distribution in the stack of a solid oxide fuel cell. Towards this end, a three dimensional modeling of the flow through a Solid Oxide Fuel Cell (SOFC) stack was carried out using the CFD analysis. This paper examines the efficacy of using cold flow analysis to describe the flow through a SOFC stack. It brings out the relative importance of temperature effect and the mass transfer effect on the SOFC manifold design. Another feature of this study is to utilize statistical tools to ascertain the extent of uniform flow through a stack. The results showed that the cold flow analysis of flow through SOFC might not lead to correct manifold designs. The results of the numerical calculations also indicated that the mass transfer across membrane was essential to correctly describe the cathode flow, while only temperature effects were sufficient to describe the anode flow in a SOFC.

• Proceedings of the KSME Conference
• /
• 2000.04b
• /
• pp.144-147
• /
• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• Speech Sciences
• /
• v.11 no.2
• /
• pp.247-257
• /
• 2004

There has been many research efforts to overcome the problems of speech recognition in the noisy conditions. Among them, the model-based compensation methods such as the parallel model combination (PMC) and vector Taylor series (VTS) have been found to perform efficiently compared with the previous speech enhancement methods or the feature-based approaches. In this paper, a data-driven model compensation approach that adapts the HMM(hidden Markv model) parameters for the noisy speech recognition is proposed. Instead of assuming some statistical approximations as in the conventional model-based methods such as the PMC, the statistics necessary for the HMM parameter adaptation is directly estimated by using the Baum-Welch algorithm. The proposed method has shown improved results compared with the PMC for the noisy speech recognition.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.243-243
• /
• 2000

This paper introduces a visual inspecting and monitoring system based on an image processing technique. We propose an image processing method for analyzing landslide movement in real time. The method adopts Laplacian of Gaussian operator to extract linear features for the captured images and uses a linear matching algorithm to distinguish the matching error for those features. When the algorithm is processed, motion parameters such as displacement area and its direction are computed. Once movement is recognized, displacements are estimated graphically with statistical amount in the image plane. The simulation results are shown us to verify the effectiveness of the developed method.