• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.692-695
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• 2000

This paper is concerned with Accuracy Design of LM Guide System in Machine Tools. Elastic deformation of bearing is calculated by Hertz contact theory and motion error of LM block is analyzed. A new algorithm using block stiffness is proposed fur the analysis of motion accuracy of the table. The best advantage of this algorithm is fast analysis speed because it isn't necessary iteration processes for satisfying equilibrium equation of the table. Motion errors of the table analyzed under artificial form error of rail theoretically and experimentally. Only one of two rails is bent by putting a thickness gauge into horizontal direction. This form error of rail is measured by gap sensor against the other rail. Then, motion errors of the table are predicted by proposed new algorithm theoretically and measured by laser interferometer. Measurements are carried out by changing the preload and thickness. The results show that the table motion errors are reduced from 1/2 to 1/60 times than form error of rail according to its height and width. And the effect of preloading is almost negligible.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.2
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• pp.60-67
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• 2004

For improving the motion accuracy of hydrostatic tables, a corrective machining algorithm is proposed in this paper. The algorithm consists of three main processes. The reverse analysis is performed firstly to estimate the rail profile from the measured linear and angular motion error, in the algorithm. For the next step, the corrective machining information is obtained based upon the estimated rail pronto. Finally, the motion errors on the correctively machined rail are analyzed by using the motion error analysis method. These processes are iterated until the analyzed motion errors are satisfactory within the target accuracy. In order to verify the validity of the algorithm theoretically, the motion errors calculated by the estimated rail after the corrective machining process, are compared with those by the true rail which is previously assumed as the initially measured value. The motion errors calculated using the estimated rail show good agreement with the assumed values, and it is shown that the algorithm is effective in acquiring the corrective machining information to improve the accuracy of hydrostatic tables.

• Journal of the Korean Society of Industry Convergence
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• v.13 no.4
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• pp.197-203
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• 2010

Laser welding is widely used for precision welding because of superior mechanical properties and high productivity. Generally the accuracy of the welding is determined by the distribution of the bead which is affected by the structural vibrations of the equipment. This study was originated to stabilize a laser welding machine to minimize the bead distribution for the precise joining. The structural properties of the laser welding machine have been investigated to analyze the major factors of the vibrations to cause the bead distribution. The ideas for the design improvement have been applied to the simulation model to identify the effects and further to achieve the stability design and to minimize the bead distribution. The result shows that a few simple design alterations can substantially suppress the structural vibrations and improve the welding accuracy. The procedure used for this study can also be applied to similar welding equipments for improving the structural stability and the welding accuracy.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.3
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• pp.275-284
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• 2011

The accuracy simulation technology of linear motion system is introduced in this paper. Motion errors and positioning errors are simulated using informations on the design parameters of elements of linear motion system. 5 Degree-of-freedom motion error analysis algorithm utilizing the transfer function method and positioning error analysis algorithm which are main frame of accuracy simulation are introduced. Simulated motion errors are compared with experimental results for verifying the effectiveness. Then, using the proposed algorithms, simulation is performed to investigate the effects of ballscrew and linear motor on the motion errors. Finally, the influence of feedback sensor position on the positioning error is also discussed.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.29-30
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• 2022

The unit-water content has a very significant effect on the durability of the construction structure and the quality of concrete. Although there are various methods for measuring the unit-water content, there are problems of time required for measurement, precision, and reproducibility. Recently, there is an FDR sensor capable of measuring moisture content in real time through an apparent dielectric constant change of electromagnetic waves. In addition, various artificial intelligence techniques that can non-linearly supplement the accuracy of FDR sensors are being studied. In this study, the accuracy of unit-water content measurement was compared and evaluated using machine learning and deep learning techniques after normalizing the data secured in concrete using frequency domain reflectometry (FDR) sensors used to measure soil moisture at home and abroad. The result of comparing the accuracy of machine learning and deep learning is judged to be excellent in the accuracy of deep learning, which can well express the nonlinear relationship between FDR sensor data and concrete unit-water content.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.196-202
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• 2024

Currently, the second most devastating form of cancer in people, particularly in women, is Breast Cancer (BC). In the healthcare industry, Machine Learning (ML) is commonly employed in fatal disease prediction. Due to breast cancer's favorable prognosis at an early stage, a model is created to utilize the Dataset on Wisconsin Diagnostic Breast Cancer (WDBC). Conversely, this model's overarching axiom is to compare the effectiveness of five well-known ML classifiers, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), and Naive Bayes (NB) with the conventional method. To counterbalance the effect with conventional methods, the overarching tactic we utilized was hyperparameter tuning utilizing the grid search method, which improved accuracy, secondary precision, third recall, and finally the F1 score. In this study hyperparameter tuning model, the rate of accuracy increased from 94.15% to 98.83% whereas the accuracy of the conventional method increased from 93.56% to 97.08%. According to this investigation, KNN outperformed all other classifiers in terms of accuracy, achieving a score of 98.83%. In conclusion, our study shows that KNN works well with the hyper-tuning method. These analyses show that this study prediction approach is useful in prognosticating women with breast cancer with a viable performance and more accurate findings when compared to the conventional approach.

• Asia pacific journal of information systems
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• v.6 no.2
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• pp.77-105
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• 1996

The accuracy of knowledge is a major concern for expert system developers and users. Machine learning approaches have recently been found to be useful in knowledge acquisition for expert systems. However, the accuracy of concept acquired from machine learning could not be analyzed in most cases. In this paper we develop a comprehensive knowledge error analysis methodology for practical use of expert systems. Decision tree induction is an important type of machine learning method for business expert systems. Here we start to analyze with knowledge acquired from decision tree induction method, and extend the results to develop error analysis methodology for general machine learning methods. We give several examples and illustrations for these results. We also discuss the applicability of these results to multistrategy learning approaches.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.937-945
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• 2000

The assessment of machined surface is difficult because the freeform surface must be evaluated by surface fairness as well as dimensional accuracy. In this study, the machined freeform surface is modeled by interpolating the data measured on the machine tool into the mathematical continuous surface, and then the surface model is improved with the parameterization to minimize surface fairness. The accuracy reliability of the measured data is confirmed through compensation of volumetric errors of the machine tool and of probing errors. Non-uniform B-spline surface interpolation method is adopted to guarantee the continuity of surface model. Surface fairness is evaluated with the consideration of normal curvature on the interpolated surface. The validity and usefulness of the proposed method is examined through computer simulation and experiment on the machine tool.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.528-535
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• 2002

In order to achieve high precision machine tools, the research for performance enhancement of feed drive systems is required. Development of the high speed feed drive system has been a major issue for the past few decades in machine tool industries. The reduction of the tool change time as well as rapid travel time can enhance the productivity. However, the high speed feed drive system generates more heat in nature, which leads thermal expansion that has adverse effects on the accuracy of machined parts. Stick-slip friction has a great influence on the contouring accuracy of CNC machine tools. In this paper table levitation system has been developed for the stick-slip in a feed drive systems. And also, the driving position is set near the center of the main slideway. From the results, it is confirmed that yaw error and straightness can be improved.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.81-88
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• 1998

Measurement and inspection of freeform surfaces are required in reverse design processes. In the case of surface measurement using a touch probe, probe radius compensation affects measuring accuracy. But current industrial practice depends upon an operator's experience to compensate for probe radius. In this paper, an on-the-machine measuring and inspection system for freeform surfaces is studied. Probe radius compensation methodology is investigated by modeling of B-spline surfaces based on digitized data. The accuracy and reliability of the developed system is verified through various kinds of numerical simulations and on-the-machine experiments.