• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.8-13
• /
• 1997

In order to utilize the information of well-known grinding data or grinding machine, a database needs to be designed by considering the delicate property of the machine tools for the high precision and quality of the demanding specification. Among the machine tools, machining conditions of the grinding are various and knowledge repeatance obtained form the grinding process are less credable.Therefore it is desirable for D/B, which is used to set the grinding conditions, to utilize the maximum machine tool capability. The present paper studied occurance limit of chatter vibration and burn considering the characteristics of machine tool. And also basic experiments were performed to establish optimum grinding canditions which can maximize the machining efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.10a
• /
• pp.60-63
• /
• 1997

Recently, factory automation and shop floor control system need a web based remote monitoring technology to control effectively machine tool. This paper describes a web based remote monitoring system which is concerned with open architecture controller for machine tool. The environment of this system consists of a lot of elements such as web server, database, machine tool, pc based controller, client computers and script programs, also which is interconnected by network including intranet or internet. Designed script programs, also which is interconnected by network including intranet or internet. Designed script program service current status and faults information of machine to remote users who want to monitor machine tool. Additionally those have various functions to service we board for q&a, downloading data and information of after-service managers.

• Korean Journal of Computational Design and Engineering
• /
• v.5 no.2
• /
• pp.136-143
• /
• 2000

The appearance of new machine tools with higher flexibility is in need of a basic structure design system for establishing the systematic and rationalized design and manufacturing procedures. In this study. the basic structure design system for machine tools is realized based on the modular construction method. Machine tools are represented as a whole and modular complex with the directed graph, and all possible structural configurations and codes of machine tools for satisfying the machining requirement are derived from the DNA data and connecting patterns of basic structural elements. Especially the structural configurations of machine tools are visualized by the solid modeling techniques and 3-D graphics techniques.

• Fashion & Textile Research Journal
• /
• v.4 no.6
• /
• pp.550-556
• /
• 2002

The changes of the main body temperature of a I tube 2 chamber bent silkworm type dyeing machine and the reduction of energy consumption of the dyeing machine by the energy saving design are reported. This dyeing machine was developed for the purpose of the energy saving and high efficiency. In this study, the changes of the main body temperature of the 1 tube 2 chamber bent silkworm type dyeing machine were studied experimentally. Especially the effect of the blower motor electric current and the main body pressure at various blower frequencies were studied experimentally. In the experimental data for the changes of main body temperature, it was shown that the main body temperature increased as the blower motor electric current and the main body pressure increased.

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.11
• /
• pp.82-90
• /
• 1995

This paper pressents a condition-based maintenance (CBM) method through bibration analysis. The well known frequency analysis is employed for performing machine fault diagnosis. The statistical control chart is also applied for analyzing the trend of the bearing wear. Vibration sensors are attached to prototype machine and signals are continuously monitored. The sampled data are utilized to evaluate how well the fast fourier transform(FFT) and the statistical control chart techniques could be used to identify defects of machine and to analyze the machine degradation. Experimental results show that the propowed approach could classify every mal-function and could be utilized for real machine diagnosis system.

• 한국데이터정보과학회:학술대회논문집
• /
• 2005.10a
• /
• pp.161-169
• /
• 2005

In this paper we propose a fuzzy c-regression model based on weighted least squares support vector machine(LS-SVM), which can be used to detect outliers in the switching regression model while preserving simultaneous yielding the estimates of outputs together with a fuzzy c-partitions of data. It can be applied to the nonlinear regression which does not have an explicit form of the regression function. We illustrate the new algorithm with examples which indicate how it can be used to detect outliers and fit the mixed data to the nonlinear regression models.

• Journal of the Korean Statistical Society
• /
• v.33 no.1
• /
• pp.25-34
• /
• 2004

In this paper we propose a prediction method on the regression model with randomly censored observations of the training data set. The least squares support vector machine regression is applied for the regression function prediction by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed prediction method.

• Journal of the Korean Data and Information Science Society
• /
• v.17 no.3
• /
• pp.821-830
• /
• 2006

This paper develops support vector based fuzzy linear and nonlinear regression models and applies it to forecasting the exchange rate. We use the result of Tanaka(1982, 1987) for crisp input and output. The model makes it possible to forecast the best and worst possible situation based on fewer than 50 observations. We show that the developed model is good through real data.

• KEPCO Journal on Electric Power and Energy
• /
• v.7 no.2
• /
• pp.301-307
• /
• 2021

After the spread of the data collection devices such as smart meters, energy data is increasingly collected in a variety of ways, and its importance continues to grow. However, due to technical or practical limitations, errors such as missing or outliers in the data occur during data collection process. Especially in the case of customer-related data, billing problems may occur, so energy companies are conducting various research to process such data. In addition, efforts are being made to create added value from data, which makes it difficult to provide such services unless reliability of data is guaranteed. In order to solve these challenges, this research analyzes prior research related to bad data processing specifically in the energy field, and propose new missing value processing methods to improve the reliability and field utilization of energy data.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.4
• /
• pp.739-748
• /
• 2012

In this paper we propose a mixed effects least squares support vector machine (LS-SVM) for the censored data which are observed from different groups. We use weights by which the randomly right censoring is taken into account in the nonlinear regression. The weights are formed with Kaplan-Meier estimates of censoring distribution. In the proposed model a random effects term representing inter-group variation is included. Furthermore generalized cross validation function is proposed for the selection of the optimal values of hyper-parameters. Experimental results are then presented which indicate the performance of the proposed LS-SVM by comparing with a standard LS-SVM for the censored data.