• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1997.10a
• /
• pp.213-218
• /
• 1997

Thermal deformation of machine origin of machine tools due to internal and external heat sources has been the most important problem to fabricate products with higher accuracy and performance. In order to solve this problem, GMDH models were constructed to estimate thermal deformation of machine origin for a vertical machining ceneter through measurement of temperature data of specific points on the machine tool. These models are nonlinear equations with high-order polynomials and implemented in a multilayered perceptron type network structure. Input variables and orders are automatically selected by correlation and optimization procedure. Sensors with small influence are deleted automatically in this algorithm. It was shown that the points of temperature measurement can be reduced without sacrificing the estimation accuracy of $\pm$5${\mu}{\textrm}{m}$. From the experimental result, it was confirmed that GMDH methodology was superior to least square models to estimate the thermal behavior of machine tools.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.781-784
• /
• 2005

The feed drive inclination significantly influences product quality, machine tool accuracy and life time. However, the accurate measurement of the inclination needs the skilled engineers and the accurate leveling instruments such as spirits or electric levels. In this study a novel methodology for the estimation of inclination angle of machine tool feed drive is proposed. The proposed methodology utilizes the motor current signals and a new mathematical model of machine tool feed drive considering inclination. The experiment results showed that the proposed method successfully estimates the inclination angle, as well as newly proposed model also enhances the accuracy of the machine tool feed drive model by introducing the inclination effects.

• Journal of Korea Multimedia Society
• /
• v.22 no.12
• /
• pp.1430-1437
• /
• 2019

In this paper, we proposed a methodology for estimating rainfall intensity using a W-band FMCW automotive radar signal which is the core technology of autonomous driving car. By comparing and analyzing the results of rainfall and non-rainfall observation, we found that the reflection intensity of the automotive radar is changed with rainfall intensity. We could confirm the possibility of deriving the quantitative precipitation estimation using the methodology derived from this result. In addition it can be possible to develop a new paradigm of precipitation observation technique by observing various events together with the weather radar and the ground rainfall observation equipment.

• International Journal of Precision Engineering and Manufacturing
• /
• v.3 no.4
• /
• pp.94-100
• /
• 2002

The conventional sliding mode control (SMC) technique requires a priori knowledge of the upperbounds of disturbances and/or modeling uncertainties to assure robustness. This, however, may not be easy to obtain in practical situation. This paper presents a new methodology, a sliding mode control with disturbance estimator (SMCDE), which offers a robust control performance without a priori knowledge about the disturbance. The proposed technique is featured by an average value of the imposed disturbance over a certain period. A nonlinear spring-mass-damper system and a two-link robot system are adopted as illustrative application examples. Control performances such as estimation error and tracking error are compared between the proposed methodology and conventional scheme.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.5
• /
• pp.848-853
• /
• 2007

This paper presents a methodology of estimating incomplete information in electricity markets for analyzing the gaming behavior of Generating Companies (GENCOs). Each GENCO needs to model its opponents' unknown information of strategic biddings and cost functions. In electricity markets with complete information, each GENCO knows its rivals' payoff functions and tries to maximize its own profit at Nash equilibriurnl Nli) by acknowledging the rivals' cost function. On the other hand, in the incomplete information markets, each GENCO lacks information about its rivals. Load patterns can change continuously due to many factors such as weather, price, contingency, etc. In this paper, we propose the method of the estimation of the opponents' cost function using market price, transaction quantities. and customer load patterns. A numerical example with two GENCOs is illustrated to show the basic idea and effectiveness of the proposed methodology.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.173.1-173
• /
• 2001

This paper proposes the methodology in image processing algorithm that estimates the pose of the pipe crawling robot. The pipe crawling robots are usually equipped with a lighting device and a camera on its head for monitoring and inspection purpose. The proposed methodology is using these devices without introducing the extra sensors and is based on the fact that the position and the intensity of the reflected light varies with the robot posture. The algorithm is divided into two parts, estimating the translation and rotation angle of the camera, followed by the actual pose estimation of the robot. To investigate the performance of the algorithm, the algorithm is applied to a sewage maintenance robot.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.26 no.3
• /
• pp.115-121
• /
• 2014

HVAC&R system costs can often be one of the most expensive components, representing approximately 15% of the total construction cost for office buildings. Despite their significant importance, there is a lack of a consistent and homogeneous framework to approximate the estimate research. This research deals with the prediction methodology of HVAC&R system cost with the aim of establishing a common idea for the analysis of the construction cost estimate. Our approach deals with the concept of an HVAC&R set that is composed of subsystems. The matrix combination analysis is examined, and total 960 HVAC&R system cost estimation can be implemented to large scale office buildings.

• Journal of Industrial Technology
• /
• v.33 no.A
• /
• pp.41-48
• /
• 2013

A statistical downscaling methodology has been developed to investigate future daily wind speeds over South Korea. This methodology includes calibration of the statistical downscaling model by using large-scale atmospheric variables encompassing NCEP/NCAR reanalysis data, validation of the model for the calibration period, and estimation of the future wind speed based on the general circulation model (GCM) outputs of scenario A1B of the CGCM3. Based on the scenario A1B of the CGCM3 model, the potential impacts of climate change on the daily surface wind speed is relatively small (+/- 1m/s) in South Korea.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.1
• /
• pp.1-6
• /
• 2016

Domain analysis is an important component for reliability of development project. Domain analysis error have an effect in the whole system. As a result, the system reliability will be deteriorated. Therefore, we need a methodology to analyze domain characteristic for a reliable analysis in the domain analysis phase. In this paper, we propose a methodology for domain categorization and estimation of complexity for reliability improvement of domain analysis.

• International Journal of Reliability and Applications
• /
• v.2 no.1
• /
• pp.27-36
• /
• 2001

This Paper proposes a new methodology for assessing the reliability of an accident management, which Is based on the reliability physics and the scheme to generate dynamic event tree. The methodology consists of 3 main steps: screening; uncertainty propagation; and probability estimation. Sensitivity analysis is used for screening the variables of significance. Latin Hypercube sampling technique and MAAP code are used for uncertainty propagation, and the dynamic event tree generation method is used for the estimation of non-success probability of implementing an accident management strategy. This approach is applied in assessing the non-success probability of implementing a cavity flooding strategy, which is to supply water into the reactor cavity using emergency fire systems during the sequence of station blackout at the reference plant.