• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.172-179
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• 1998

To quickly determine the effect of the substitute component on the machine's performance is very important in the design and manufacturing processes. And minimizing machine cost and maximizing machine quality mandate predictability of machine accuracy. In this study, in order to evaluate the effects of the component's geometric errors and dimensions on the machining accuracy of gantry-type 5-axis machining centers, a geometric error analysis and virtual manufacturing system are developed based on the mathematical model for the shape generation motion of machine tool considering the component's geometric errors and dimensions, the solid modeling techniques and so on.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.1
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• pp.27-32
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• 2011

These days more electric devices are implemented in car, and more accurate estimation of SoC is required. OCV with current integration and Internal Resistance is essential method of Battery SoC Estimation. In this paper we propose OCV with current integration method and compare with Internal Resistance method. In OCV with current integration method estimation error was less than average 2%, but requires more than 5 minutes to stabilize OCV. If Stop and Running conditions are change frequently, estimation error will increase. In Internal resistance Modeling method, in high SoC state, estimation error was more than 15%, and in low SoC state, estimation error was less than 8%.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2485-2487
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• 2000

In this paper, we use a fuzzy algorithm to detect and diagnose the error which is caused by time delay of the computer-controlled system. Generally, a computer-controlled system is composed of computer and process. And they communicate the data each other. In data communication, error occurs by some reasons, such as noise, disturbance, hardware defect, etc. Time delay is one of the reasons. And time delay makes it difficult to distinguish whether the system really has a problem or not. Therefore, we need to detect and diagnose the error from time delay. For difficulty of modeling and ambiguity of classification, we use a fuzzy algorithm. To verify the better performance of the proposed algorithm, we exemplified by some simulation results.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.2
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• pp.121-127
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• 2008

Micro end-milling has been becoming an important machining process to manufacture a number of small products such as micro-devices, bio-chips, micro-patterns and so on. Despite the importance of micro end-milling, many related researches have given grand efforts to micro end-milling phenomenon, for example, micro end-milling mechanism, cutting force modeling and machinability. This paper strongly concerned actual problem, micro tool deflection, which causes excessive machining errors on the workpiece. To solve this problem, machining error prediction method was proposed through a series of test micro cutting and analysis of their SEM images. An iterative algorithm was applied in order to obtain corrected tool path which allows reducing machining errors in spite of tool deflection. Experiments are carried out to validate the proposed approaches. In result, remarkable error reduction could be obtained.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.59-66
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• 2005

In this paper, a robust stationary Kalman filter is designed by minimizing selected performance indices so that it is less sensitive to uncertainties. The uncertainties include not only stochastic factors such as process noise and measurement noise, but also deterministic factors such as unknown initial estimation error, modeling error and sensing bias. To reduce the effect on the uncertainties, three performance indices that should be minimized are selected based on the quantitative error analysis to both the deterministic and the stochastic uncertainties. The selected indices are the size of the observer gain, the condition number of the observer matrix, and the estimation error variance. The observer gain is obtained by optimally solving the multi-objectives optimization problem that minimizes the indices. The robustness of the proposed filter is demonstrated through the comparison with the standard Kalman filter.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.66.6-66
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• 2001

In this paper, we studied the error compensation using an error budget method for repeatability improvement of the precision positioning system. The precision positioning system is developed for micro-pressing machine. We performed the force and displacement analysis about parts of the system. Proposed system determines the position and orientation of the materials manufactured by micro-pressing machine. It is consisted of x-y-z linear stages setting the position, and the gripper system setting the orientation. We executed kinematic and dynamic modeling of the whole precision positioning system. By generalizing the design variables, precision positioning system has the flexibility of material dimension. As we tried an error compensation using ...

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2168-2177
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• 2018

The unavoidable forecast error of wind power is one of the biggest obstacles for wind farms to participate in day-ahead electricity market. To mitigate the deviation from forecast, installation of energy storage system (ESS) is considered. An accurate model of wind power forecast error is fundamental for ESS sizing. However, previous study shows that the error distribution has variable kurtosis and fat tails, and insufficient measurement data of wind farms would add to the difficulty of modeling. This paper presents a comprehensive way that makes the use of mixed skewness model (MSM) and copula theory to give a better approximation for the distribution of forecast error, and it remains valid even if the dataset is not so well documented. The model is then used to optimize the ESS power and capacity aiming to pay the minimal extra cost. Results show the effectiveness of the new model for finding the optimal size of ESS and increasing the economic benefit.

• International Journal of Automotive Technology
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• v.8 no.2
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• pp.225-232
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• 2007

A tooth profile modification for loaded gears is used to avoid a tooth impact. Since a tooth profile error causes amplification of the cumbersome whine noise in automotive gear transmissions, an optimal quantity of tooth profile modifications must be obtained for good performance in the vibration sense. In this paper, a tooth profile modification curve considering profile manufacturing errors and elastic deformation of the gear tooth is formulated; in addition, transmission errors of the gear system with modified teeth are verified. The equivalent excitation due to transmission errors is formulated. For experimental evaluation of the transmission error, the transmission error for a simple gear system was measured by two rotational laser vibrometers. Finally, we perform a comparative analysis between the calculated and measured responses to the excitations due to the transmission error to verify the practicability of the application to automotive transmissions.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.294-298
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• 2009

In this study, we proposes the method to improve the quality of the image through the edge extraction more delicately. Our method is named ESII(Edge Sensitive Image Interpolation) and doesn't use the fixed parameter of the interpolation kernel. However, it changes the parameter of pixel which is interpolated to the high definition image using the proper information from the surrounding pixels. It reconstructs the image by using the LSE(Least Square Error) and determining the pixel values to make the CME(Camera Modelling Error) minimized. Compared to the conventional methods, suggested method shows the higher quality of subjective and objective image definition and lessons the computational complexity by separating the image into 1-D data.

• Spatial Information Research
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• v.21 no.2
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• pp.45-54
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• 2013

Analytical and simulation error models have the ability to describe (or realize) error-corrupted versions of spatial data. But the different approaches for modeling positional errors require an internal validation that ascertains whether the analytical and simulation error models predict correct positional errors in a defined set of conditions. This paper presents stochastic simulation models of a point and a line segm ent to be validated w ith analytical error models, which are an error ellipse and an error band model, respectively. The simulation error models populate positional errors by the Monte Carlo simulation, according to an assumed error distribution prescribed by given parameters of a variance-covariance matrix. In the validation process, a set of positional errors by the simulation models is compared to a theoretical description by the analytical error models. Results show that the proposed simulation models realize positional uncertainties of the same spatial data according to a defined level of positional quality.