• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1401-1406
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• 2014

Knowledge of the manufacturing process of semiconductor devices in order to obtain a copper pattern using chemical mechanical polishing (CMP) planarization using a Wafer polishing process is applied with a thickness of the copper measured in real time, which need to be precisely controlled by, where the acquisition the actual thickness of the sensor value with the calculated value in terms of error can occur in the process. Approximated the actual measurement values so as to obtain a method using a simple average, moving average, compared to the results using filters onggo Strom real-time measurements of the thickness of the units of the control system to reduce the variation in the implementation of the method described for the.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.120-126
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• 2019

Recently, there is an increasing need for highly precise processing with the rapid development of precision machinery, electrical and electronics, and semiconductor industries. Cutting machine control relies on the operator's sense and experience in tradition, but it has been greatly enhanced by the adoption of CNC(Computerized Numeric Controller). In addition, cutting dynamics technology has been paid attention to reflect the operating state of machine in real time. This paper presents a method to detect and stabilize tool vibration by attaching an acoustic sensor to a CNC machine. The sensed acoustic data is synchronized with the tool position and the abnormal vibration frequency is separated from the collected acoustic frequency, then analyzed to detect the tool vibration. Also the reliability the tool vibration detection and stabilization is improved by applying the cutting dynamic method. The proposed method is analyzed and evaluated in terms of the surface roughness.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.111-118
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• 2023

For the implementation of a smart factory, it is necessary to collect data by connecting various sensors and devices in the manufacturing environment and to diagnose or predict failures in production facilities through data analysis. In this paper, to predict the residual useful lifetime of milling insert used for machining products in CNC machine, weight k-NN algorithm, Decision Tree, SVR, XGBoost, Random forest, 1D-CNN, and frequency spectrum based on vibration signal are investigated. As the results of the paper, the frequency spectrum does not provide a reliable criterion for an accurate prediction of the residual useful lifetime of an insert. And the weighted k-nearest neighbor algorithm performed best with an MAE of 0.0013, MSE of 0.004, and RMSE of 0.0192. This is an error of 0.001 seconds of the remaining useful lifetime of the insert predicted by the weighted-nearest neighbor algorithm, and it is considered to be a level that can be applied to actual industrial sites.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.11-16
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• 2019

This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1243-1248
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• 2018

Metal Powder Metallurgy is a manufacturing technology that makes unique model parts or a certain type of product by using a hardening phenomenon when a powder of metal or metal oxide is put it into a mold and compression-molded by a press and then heated and sintered at a high temperature. Powder metallurgical press equipment is mainly used to make the parts of automobile, electronic parts and so on, and most of them are manufactured using precise servo motor. The intelligent precision servo control powder molding press system which is designed and implemented in this paper has advantages of lowering the price and maintaining the precision by using the mechanical camshaft for the upper ram part and precisely controlling the lower ram part using the high precision servo system. In addition, OPC-based monitoring and process data collection systems are designed and implemented to provide scalability that can be applied to smart manufacturing management systems that utilize Big Data in the future.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3501-3505
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• 2007

As the power plant industry has been changed into competition structure, power generation companies do more with less by increasing capacity and lowering operation costs. In order to achieve this goals, an on-line real-time performance monitoring system has been needed to introduced to fossil power plant. The system represents a suite of related software modules which consist of on-line data, and on-line performance modules. This system can help the plant staff get the most out of their facilities by continuously monitoring deviations in equipment performance and the impact on those deviations on plant power, heat rate and operating cost. This paper shows the comparison of design value with acceptance test and current(measured) value.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.696-701
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• 2004

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion, have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• 기계와재료
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• v.21 no.3
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• pp.32-41
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• 2009

공기압 액추에이터는 자동화 생산라인 등의 다양한 산업분야에서 사용되고 있으며, 고장이 발생하면 전체 시스템에 막대한 손실을 야기 시킬 수 있는 부품이다. 그러나 기존 공기압 액추에이터에 대한 연구는 설계 관점에서의 연구나 특성해석 및 구동속도 등의 제어관점에서의 연구가 대부분이었으며, 실린더의 수명과 신뢰성에 대한 연구는 거의 이루어지지 않았다. 이와 연관하여 최근 공기압 액추에이터의 신뢰성에 대한 중요성 및 소비자의 요구수준이날로 증대되고 있으며, 최근 공기압 액추에이터의 수명분포 데이터를 분석과 가속수명시험 실시를 통한 수명분포 추정과 형상모수의 동일성 검정, 제안한 복합가속 수명시험 모델에 대한 유용성 검증 등의 연구와 ISO를 중심으로 규격화를 위한 활동이 활발히 진행되고 있다. 따라서 공기압 액추에이터에 대한 신뢰성 평가기법 및 가속수명 시험평가 기술에 대한 기술적 접근법을 소개하고자 한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.806-811
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• 1994

최근의 절삭가공 생산시스템은 무인자동화,고속화,정밀화로 대별되면서 생산성을 극대화시킬려는 방향으로 연구 가 진행되고 있다. 종래의 CNC화된 기계가공시스템에서는 절삭속도,이송속도 그리고 절삭깊이 등과 같은 절삭 조건은 On-line으로 조절되는 장치를 갖지 않고 Off-line으로 프로그래머의 경험이나 절삭가공의 데이터 핸드북을 통하여 결정되어진다. 이러한 절삭조건은 절삭률 즉 생산성의 측면에서 최적의 값이 될 수가 없다. 이는 프로그래머가 측면에서 최적의 값이 될 수가 없다. 이는 프로그래머가 공구의 마모나 표면거칠기, 또는 공작기계의 부하 등을 고려하여 극적으로 NC프로그램을 짜기 때문이다. 이러한 문제점 때문에 현재 개발되어지고 있는 대부분의 적응제어시스템은 실용화가 되지못하고 있는 실정이어서 효휼적인 적응시스템의 개발은 필수적이다. 따라서 본 연구에서는 무인자동화 가공시스템에서 생산성을 최대화하기 위하여 사용하는 ACO 시스템에서 발생하는 상기의 문제를 해결하여 실용화할 수 있는 가공 최적화 시스템을 개발함을 연구의 목적으로 하고 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.901-904
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• 2020

본 시스템은 세 단계의 모델을 복합적으로 구성하여 이루어진다. 첫 단계로 사람의 음성언어를 텍스트로 전환한 후 사용자의 발화 의도를 분류해내는 BoW방식을 이용해 인간의 명령을 이해할 수 있는 자연어 처리 알고리즘을 구성한다. 이후 YOLOv3-tiny를 이용한 실시간 영상처리모델과 OctoMapping모델을 활용하여 주변환경에 대한 3차원 지도생성 후 지도데이터를 기반으로하여 동작하는 기구제어 알고리즘 등을 ROS actionlib을 이용한 관리자시스템을 구성하여 ROS와 딥러닝을 활용한 편리한 인간-로봇 상호작용 시스템을 제안한다.