• Journal of Advanced Navigation Technology
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• v.9 no.2
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• pp.140-146
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• 2005

In this paper, we proposed the frequency offset compensation algorithm and tracking algorithm which could improve the accumulated phase error for HDR-WPAN system. The proposed frequency offset compensation technique estimated each sample phase error by autocorrelation characteristics of CAZAC sequence, estimated phase error multiple each sample in a symbol, and finally compensated for the frequency offset. After frequency offset compensation using two steps, coarse and fine frequency offset, tracking algorithm have to use to compensate for the accumulated phase error. Because there is no pilot symbol in payload, more phase rotation occurred in received signal constellations due to the accumulated phase error as the payload length increase. Tracking algorithm compensates for a cumulative phase error ${\theta}$ between payload data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.297-302
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• 1997

Linear displacement accuracy is one of the most important factors that determine machine tool accuracy. The laser interferometer has been usually recommended for the measurement of linear displacement accuracy. In this paper, microcomputer aided measurement and compensation system has been developed forthe pitch error in a CNC machine tool. For accurate pitch error calculation, the analysis code for the pitch error has been also implemented according to the international standards(ISO). The PC based automatic compensation system for the pitch error is also implemented. A new algorithm for calculating optimum value for pitch error compensation is proposed, minimizing the deviation at each target points. The development system has been applied to a practical CNC maching center and the performance has been demonstrated.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.728-733
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• 2009

This paper presents the compensation of mechanical deflection error in SCARA robot. End of robot gripper is deflected by weight of arm and pay-load. If end of robot gripper is deflected constantly regardless of robot configuration, it is not necessary to consider above mechanical deflection error. However, deflection in end of gripper varies because that moment of each axis varies when robot moves, it affects the relative accuracy. I propose the compensation method of deflection error using neural network. FEM analysis to obtain the deflection of gripper end was carried out on various joint angle, the results is used in neural network teaming. The result by simulation showed that maximum relative accuracy reduced maximum 9.48% on a given working area.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1352-1357
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• 2004

Thermal error compensation has been developed for CNC (Computer Numerical Control) machining center with moving heat sources. The thermal error in CNC machining center has an effect on machining accuracy more than the geometric error does. Thus, temperature distributions of a spindle unit have been analyzed numerically by a Finite Differential Method and experimentally by an infrared (IR) camera in this study. A multiple variable method has been derived to estimate the thermal deformation of the machine origin stably and effectively after measuring deformation and temperature data. The experimental results for a vertical machining center have shown that the thermal errors of the machine origins were reduced more than 30% by the developed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.327-332
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• 2009

This paper proposes a method to improve the accuracy of a short-term electrical load forecasting (STLF) system based on neuro-fuzzy models. The proposed method compensates load forecasts based on the error obtained during the previous prediction. The basic idea behind this approach is that the error of the current prediction is highly correlated with that of the previous prediction. This simple compensation scheme using error information drastically improves the performance of the STLF based on neuro-fuzzy models. The viability of the proposed method is demonstrated through the simulation studies performed on the load data collected by Korea Electric Power Corporation (KEPCO) in 1996 and 1997.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.99-106
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• 2002

This paper proposes an error compensation method that improves accuracy with geometry information of injection molding parts. Geometric information can give an improved accuracy in reverse engineering. Measuring data can not lead to get accurate geometric model, including errors of physical parts and measuring machines. Measuring data include errors which can be classified into two types. One is molding error in product, the other is measuring error. Measuring error includes optical error of laser scanner, deformation by probe forces of CMM and machine error. It is important to compensate these in reverse engineering. Least square method (LSM) provides the cloud data with a geometry compensation, improving accuracy of geometry. Also, the functional shape of a part and design concept can be reconstructed by error compensation using geometry information.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.122-129
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• 1999

A 5-axis CNC machine tool is more useful compared with a 3-axis machine tool, because the position and the orientation of a tool tip can be controlled simultaneously. Unlike the 3-axis machine tool, the 5-axis machine tool has the volumetric position error and volumetric orientation error due to the quasi-static error of each machine tool joint which is a major source of machined part error. So, the generalized error synthesis model of the 5-axis CNC machine tool was developed to predict and to compensate for the volumetric position error and the volumetric orientation error. It was proposed that a compensation algorithm to correct simultaneously the volumetric position error and the volumetric orientation error of the 5-axis CNC machine by error inverse kinematic.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.187-192
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• 1993

Thermal deformation causes large amount of machine tool errors. In order to compensate for thermal and geometric errors of the machine tool an off-line geometric adaptive control (GAC) scheme was developed. THe GAC method was realized by using a measuring plate made of precision spheres. Error vectors and volumetric errors were measured by the measuring plate. Error compensation models were obtained from error vectors and a kinematic chain of machine tools. Reliability of the GAC system of thermal and geometric errors were confrimed by large amount of experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.636-643
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• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.4
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• pp.117-122
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• 2000

This paper presents an indirect compensation of thermal errors during machining , in which thermal error is modelled as a linear regression of temperatures measured at 4 specified positions. In this regression model, weighting coefficients of the measured temperatures were estimated by using the least square method. The grinding test with compensation , after 4 -hour warning-up operation before the test, showed that the maximum machining error of the work pieces was reduced to 12${\mu}{\textrm}{m}$ while it measured by 28${\mu}{\textrm}{m}$ without compensation . Furthermore the standard deviation of machining errors was also reduced from 8${\mu}{\textrm}{m}$ to 2${\mu}{\textrm}{m}$.