• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.101-106
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• 2004

Measurements of linear motion accuracy for one axis of NC lathe have achieved with laser interferometer system, but measurement of plane motion accuracy for two axes on zx-plane of NC lathe have not achieved with the above system. Therefore in this study, measuring unit system is organized using two optical linear scales in order to acquire error. data during of plane motion of ATC(Automatic Tool Change.) of NC lathe by reading zx-plane coordinates. Two optical linear scales of measuring unit are fixed on zx-plane of NC lathe, and moving part of the scales are fixed to the ATC and then error motion data of z, x-coordinates of the ATC are received from the scales through the PC counter card inserted in computer at constant time intervals using tick pulses coming out from computer. And then, error motion data files acquired from measuring are saved in computer memory and the aspect of plane motion are modeled to plots, and range of the error data, means. average deviations, and standard deviations etc. are calculated by means of statistical treatments using computer programs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.471-479
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• 2019

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.245-251
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• 2019

Sonar bearing accuracy is the correspondence between the target orientation predicted by sonar and actual target orientation, and is obtained from measurements. However, when measuring sonar bearing accuracy, many errors are included in the results because they are made at sea, where complex and diverse environmental factors are applied. In particular, parallax error caused by the difference between the position of the GPS receiver and the sonar sensor, and the time delay error generated between the speed of underwater sound waves and the speed of electromagnetic waves in the air have a great influence on the accuracy. Correcting these parallax errors and time delay errors without an automated tool is a laborious task. Therefore, in this study, we propose a sonar bearing accuracy measurement equipment with parallax error and time delay error correction. The tests were carried out through simulation data and real data. As a result of the test it was confirmed that the parallax error and time delay error were systematically corrected so that 51.7% for simulation data and more than 18.5% for real data. The proposed method is expected to improve the efficiency and accuracy of sonar system detection performance verification in the future.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.3
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• pp.58-66
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• 1995

It is very important to test motion accuracy and performance of NC machine tools as they affect that of all other machines machined by them in industry. In this paper, in has become possible to detect errors of linear displacement of radial direction for circular motion test using newly assembled magnetic type of linear scales so called Magnescale ball bar system, and to calculate time interval getting error motion data and revolution angle of circular motion in machining center using tick pulses come out from computer. And a set of error data gotten from test is expressed to a plot by computer treatment and to numerics of error motion by statistical treatment and results of test are compared with those of Renishaw ball bar system.

• 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 Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.417-422
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• 2002

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. In this study, the compensation device and temperature-based algorithm have been implemented on the machining center in order to compensate thermal error of machine tools under the real-time. The thermal errors are predicted using the neural network and multi-regression modeling methods. In order to compensate thermal characteristics under several operating conditions, experiments performed with five gap sensors and manufactured compensation device on the horizontal machining center.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1784-1788
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• 2003

For the improvement of geometrical accuracy in end milling, cutting method and cutting condition selection are investigated in this paper. As machining processes are composed of several steps such as roughing, semi-finishing. and finishing, cutting forces and tool deflection are calculated considering surface shape generated by the previous cutting. The effects of tool teeth numbers, tool geometry, and cutting conditions on the form error are analyzed. Using the from error prediction method from tool deflection, cutting condition for geometrical accuracy improvement is discussed. The characteristics and the difference of generated surface shape in up and down milling are dealt with and over-cut free condition in up milling is presented. The form error reduction method by alternating up and down milling is also suggested. The effectiveness of the presented method is examined from a set of cutting tests under various cutting conditions. This research contributes to cutting process optimization for the geometrical accuracy improvement in die and mold manufacture.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.143-147
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• 1998

As the accuracy of manufactured goods needed high-accuracy processing has made the efficiency of NC and measurment technology develop, the innovation of machine tools has influence the development of the semi-conductor and optical technology. We can mention that a traction role of the acceleration for the development like that depends on the development of the measurement technics - Stylus instrument method, STM, SEM, Laser interferometer method - which are used for measuring the movement accuracy of machine tools. The movement error factors in movement accuracy are expressed as yaw, roll, and pitch etc. Machining center has 21 movement error factors including of 3 axies joint errors because that has 3 axies and has been measured as the standard of the unloaded condition until now inspite of getting static, dynamic, and servo-gain errors in the case of expending the error range. Therefore, this study tries to measure position accuracy according to loading on the X-Y table of the machining center.