• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.187-193
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• 2003

This paper presents an on-machine measurement method of flatness error fur surface machining processes. There are two kinds of on-machine measurement methods available to measure flatness errors in workpieces: i.e., surface scanning method and sensor scanning method. However, motion errors are often engaged in both methods. This paper proposes an idea to realize a measurement system of flatness errors and its rigorous application for estimation of motion errors of the positioning system. The measurement system is made by modifying the straightness measurement system, which consists of a laser, a CCD camera and processing system, a sensor head, and some optical units. The sensor head is composed of a retroreflector, a ball and ball socket, a linear motion guide unit and adjustable arms. The experimental .results show that the proposed method is useful to identify flatness errors of machined workpieces as well as motion errors of positioning systems.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.3
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• pp.112-118
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• 2007

Recently, the machine tools called multi-task machines, which mounted rotary axes on the table or spindle are used increasingly. Accordingly, multi-task machine tool takes a growing interest on the motion accuracy of feed drive system. In this study, measurement and diagnosis of motion errors ware attempted from circular pattern obtained by using DBB (Double ball bar) device. Those were obtained at both clockwise and counter clockwise motions in mutually perpendicularly intersecting three planes. The reliability of error measurement system for multi-task machine tool was verified by the direct test cutting.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.3
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• pp.31-37
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• 2007

Recently, the machine tools called multi-task machines, which mounted rotary axes on the table or spindle are used increasingly. Accordingly, multi-task machine tool takes a growing interest on the motion accuracy of feed drive system. In this study, measurement and diagnosis of motion errors ware attempted from circular pattern obtained by using DBB (Double ball bar) device. Those were obtained at both clockwise and counter clockwise motions in mutually perpendicularly intersecting three planes. The reliability of error measurement system for multi-task machine tool was verified by the direct test cutting.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.327-331
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• 2001

In the process of optical parts machining, polishing has been applied. Traditional polishing process is suitable for spherical optical parts. But it is very difficult to apply traditional process for aspheric optical parts. Nowadays, as growing needs for aspherical optic parts, many researches have been conducted. In this study, we developed computer controlled polishing system which consists of three major parts of active pressure control for correcting polishing process, mechanical on-machine measurement for rough polishing, and optical on-machine measurement for finish polishing, respectively. In this paper, a systematic stretegy for correcting polishing process, pressure control scheme for polishing tool, and on-machine measurement methods for automated and precise polishing are suggested. The information about developed machine is also included.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.15-21
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• 1997

This paper presented a linear motion accuracy by using two-dimensional probe with the master block and the square for NC machine tools. This measuring system could be measured motion error due to numerical control system. The results of measurement and simulation for motion error were similar, and so, this system had enough accuracy to measure a linear motion accuracy for NC machine tools. The experimental results are as follows. 1. This measuring system could be measured motion error due to mumerical control system. 2. The results of measurement and simulation for motion error were similar. 3. This measuring system had enough accuracy to measure a linear motion accuracy for NC machine tools.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.204-209
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• 1998

The acceleration of the performance of machine tools influences the development of the semi-conductor and optical technology as the development of NC and measurement 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 quasi-static error of machine tools. Because the measurement has been done to unload condition without considering of mechanical stiffness in the case of machining center as we measure the quasi-static error of machine tools on general studies, people who works on the spot has many problems on the data value. Therefor we will help working more accurately on the spot by measuring, analyzing, displaying the deflection of the table and support shaft when we load on the table and the support shaft of machining center using laser interferometer. Also we try to settle new conception of the measurement method and more accurate grasp of the deflection tendency by verifing the tendency of the error measured through the comparison of the simulated error using ANSYS, a common finite element analysis program, which is able to measure heat deformation, material deformation, and error resulted form this study.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.1
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• pp.75-84
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• 2003

In this paper, a new nano/micro-mechanical processing test machine was developed. This new test machine, which is based on the principle of the scanning force controlled probe microscope, can realize nano/micro-mechanical machining and in-process profile measurement. Experimental results of nano/micro indentation and scratching show that the controllable cutting depth of the test machine can be controlled by PZT actuator. Profile measurement of the machined surface has also been performed by using the test machine and a conventional AFM(Atomic Force Microscopy). A good agreement of the two measurement results have been achieved.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.41-52
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• 2014

In this paper, O-ring size measurement algorithm based on a small machine vision inspection equipment which can replace a expensive and large machine vision inspection equipment is presented. The small machine vision inspection equipment acquires a image from a CCD camera shooting a measurement plane which located on a back light and the proposed size measurement algorithm is apply to the image. For improvement of size measurement accuracy, camera lens distortion correction and perspective distortion correction are conducted by software technique. Consider O-ring's shape, ellipse fitting model is applied. In order to increase the reliability of ellipse fitting, RANSAC algorithm is applied.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.19-27
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• 2023

In recent times, an exponential increase in Internet traffic has been observed as a result of advancing development of the Internet of Things, mobile networks with sensors, and communication functions within various devices. Further, the COVID-19 pandemic has inevitably led to an explosion of social network traffic. Within this context, considerable attention has been drawn to research on network traffic analysis based on machine learning. In this paper, we design and develop a new machine learning framework for network traffic analysis whereby normal and abnormal traffic is distinguished from one another. To achieve this, we combine together well-known machine learning algorithms and network traffic analysis techniques. Using one of the most widely used datasets KDD CUP'99 in the Weka and Apache Spark environments, we compare and investigate results obtained from time series type analysis of various aspects including malicious codes, feature extraction, data formalization, network traffic measurement tool implementation. Experimental analysis showed that while both the logistic regression and the support vector machine algorithm were excellent for performance evaluation, among these, the logistic regression algorithm performs better. The quantitative analysis results of our proposed machine learning framework show that this approach is reliable and practical, and the performance of the proposed system and another paper is compared and analyzed. In addition, we determined that the framework developed in the Apache Spark environment exhibits a much faster processing speed in the Spark environment than in Weka as there are more datasets used to create and classify machine learning models.