• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.104-108
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• 1993

The linear length measurements are most frequently performed and should be most accurate among other parts in dimensional metrology. We developed the linear measuring system using a laser interferometer to improve the accuracy and to shorten the calibration time. The uncertainty of the system is 0.01 .mu. for 500mm steel gage block. The range of the measurement and resolution of the system are 1000mm and 0.01 .mu. m, respectively.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.20-23
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• 2002

In silicon wafer manufacturing process, the grinding process has been adopted to improve the quality of wafer such as flatness, roughness and so on. This paper describes the effect of grinding process on the surface quality of wafer. The experiments are carried out by high precision in fred grinder with air bearing spindle. The relationship between the inclination of chuck table and the flatness of wafer is investigated, and the effect of grinding conditions including wheel speed, table speed, and feed rate on damage depth and roughness of wafer is also investigated. The experimental results show that there is close relationship between the inclination of the chuck table and the flatness of wafer, and the grinding conditions within this paper little affect the flatness of wafer and relatively high affect the damage depth of wafer.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.129-134
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• 2000

This paper presents the development of ultra-precision machining process of large aspheric aluminum mirrors with a maximum diameter of 620 mm. An ultra-precision machine, "Nanoturn60", developed by Daewoo Heavy Industries Ltd. is used for machining and motion errors of the machine are compensated by using the FTS developed by IAE(Institue for Advanced Engineering) during the machining process. To check the form accuracy of machined aspheric surfaces, on-machine form measurement system is developed. This measurement system consists of air bearing touch probe, straight edge, and laser sensor. With in-process error compensation by FTS(Fast Tool Servo), aspheric mirrors with the from accuracy of submicron order are obtained. obtained.

• Smart Structures and Systems
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• v.19 no.4
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• pp.431-439
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• 2017

This investigation is aimed to develop a model of experimental-computation determination of a support moment of a cantilever beam loaded with concentrated force at its end including the optimal choice of coordinates of deflection data points and parameters of transformation of deflection data in case of insufficient accuracy of the assignment of initial parameters (support settlement, angle of rotation of the bearing section) and cantilever beam length. The influence of distribution and characteristics of sensors on the cantilever beam on the accuracy of determining the support moment which improves in the course of transition from the uniform distribution of sensors to optimal non-uniform distribution is shown. On the basis of the theory of inverse problems the method of transformation reduction at numerical differentiation of deflection functions has been studied. For engineering evaluation formulae of uncertainty estimate to determine a support moment of a cantilever beam at predetermined uncertainty of measurements using sensors have been obtained.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.3
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• pp.51-56
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• 2002

In order to achieve high precision machine tools, Performance enhancement of feed drive systems is required. One of the important technical issues is how to decrease thermal expansion of ball screw in proportion to the increase of machining speed. When measuring force of stretch of ball screw, since not only actual expansion and the value of bending have to be considered, it is impossible to define the exact value of expansion. In addition, support bearings of ball screw gain considerable force in axial direction. It also generates thermal expansion on the ball screw, and deteriorates the performances of the hearings. In conclusion, it is impossible to give the pretension enough to absorb all the elongation due to thermal expansion generated during machine is running. If given bed column and saddle are all bent to chance machine accuracy, and the support bearings of ball screw is damaged.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.54-60
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• 2013

In this paper, a novel method called location-based delivery (LBD), which combines the short message service (SMS) and global position system (GPS), is proposed, and further, a realistic system for tracking a target's movement is developed. LBD reduces the number of short message transmissions while maintaining the location tracking accuracy within the acceptable range. The proposed approach, LBD, consists of three primary features: Short message format, location prediction, and dynamic threshold. The defined short message format is proprietary. Location prediction is performed by using the current location, moving speed, and bearing of the target to predict its next location. When the distance between the predicted location and the actual location exceeds a certain threshold, the target transmits a short message to the tracker to update its current location. The threshold is dynamically adjusted to maintain the location tracking accuracy and the number of short messages on the basis of the moving speed of the target. The experimental results show that LBD, indeed, outperforms other methods because it satisfactorily maintains the location tracking accuracy with relatively fewer messages.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.769-772
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• 2005

Five DOF motion errors of a hydrostatic bearing table driven by the coreless type linear motor were compensated utilizing the active controlled capillaries in this study. Horizontal linear motion and yaw error were simultaneously compensated using two active controlled capillaries and vertical linear motion, pitch and yaw error were also simultaneously compensated using three active controlled capillaries. By the compensation, horizontal linear motion accuracy and yaw were improved from 0.16 ${\mu}m$ and 1.96 arcsec to 0.02 ${\mu}m$ and 0.03 arcsec. Vertical linear motion accuracy, pitch and roll were also largely improved from 0.18 ${\mu}m$, 2.26 arcsec and 0.14 arcsec upto 0.03 ${\mu}m$, 0.07 arcsec and 0.02 arcsec. The compensated motion errors were within the range of measuring repeatability which was ${\pm}0.02\;{\mu}m$ in the linear motion and ${\pm}0.05$ arcsec in the angular motion. From these results, it is found that the motion error compensation method utilizing the active controlled capillaries are very effective to improve the five motion accuracies of the hydrostatic bearing tables.

• Journal of the Korean Institute of Navigation
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• v.7 no.2
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• pp.1-45
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• 1983

This paper concerns the applications of the Kalman filter to navigation and the develment of computer programs of the navigational calculations. Methods to apply the Kalman filter to celestial fix, fix by cross bearing and cocked hat are proposed, and numerical simulations under various noise conditiions are conducted. The accuracy of the optimal positions obtained by the Kalman filter is compared with that of the fixed positiions by radial error method. In the case of celestial fix, an algorithm to estimate the optimal positions by using the linear Kalman filter is presented. The optimal positions by the Kalman filter are compared with the running fixes and with the most probable positions obtained from a single line of position. It is confirmed that the resutls of the proposed method are more accurate than the others. In practical piloting, bearings are generally measured intermittently and the measurement process is nonlinear. It is, therefore, difficult for us to apply the Kalman filter to fix by cross bearing. In order to be used in such an unfavorable case, the extended Kalman filter is revised and the aplicability of the revised extended Kalman filter is checked by numerical simulation under various noise conditions. In a cocked hat, an inside or outside fix is dependent only upon azimuth spread, if the error of each line of position is assumed to be equal both in magnitude and sign. A new technique of selecting a ship's position between an inside fix and an outside fix in a cocked hat by using fix determinant derived from the equation of three lines of position is also presented. The relations among the optimal position by Kalman filter, incentre (or excentre) and random error centtre of the cocked hat are discussed theoretically and the accuracy of the optimal position is compared with that of the others by numerical simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.9-17
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• 2023

In this paper, we propose a one-class vibration anomaly detection system for bearing defect diagnosis. In order to reduce the economic and time loss caused by bearing failure, an accurate defect diagnosis system is essential, and deep learning-based defect diagnosis systems are widely studied to solve the problem. However, it is difficult to obtain abnormal data in the actual data collection environment for deep learning learning, which causes data bias. Therefore, a one-class classification method using only normal data is used. As a general method, the characteristics of vibration data are extracted by learning the compression and restoration process through AutoEncoder. Anomaly detection is performed by learning a one-class classifier with the extracted features. However, this method cannot efficiently extract the characteristics of the vibration data because it does not consider the frequency characteristics of the vibration data. To solve this problem, we propose an AutoEncoder model that considers the frequency characteristics of vibration data. As for classification performance, accuracy 0.910, precision 1.0, recall 0.820, and f1-score 0.901 were obtained. The network design considering the vibration characteristics confirmed better performance than existing methods.