• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.357-363
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• 2011

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.176-177
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• 2013

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.503-504
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• 2014

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.860-861
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• 2013

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2013.10a
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• pp.158-159
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• 2013

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1593-1598
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• 2011

The purpose of this study is to perform parameter selection and develop a method for the condition monitoring of an LCD conveyance robot. To determine the vibration characteristics of the driving part of the robot, the gear mesh frequency (GMF) of the speed-reducing gearbox is calculated and confirmed by frequency analysis. In order to ensure reproducibility of the measured data, an appropriate working pattern is selected and experiments are carried out. For condition monitoring of the robot, a wireless measurement system is constructed and used in parameter selection, with the GMF as the center. A method involving the use of the standard deviation of the measured data and another method involving the use of multiple value of amplitude are proposed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.504-509
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• 1995

컴퓨터에 의한 생산시스템의 통합체계화와 온-라인화에 따라 자동화된 설비진단 방법이 요구되어지고 있다. 이에 따라 기계설비에 각종 센서를 부착하여 실시간으로 수집된 출력신호를 이용하여 기계설비를 온-라인으로 감시하는 여러가지 기법들이 제시되고 있다. 본 연구에서는 진동센서로부터의 신호를 radial 함수에 근거한 다단계 뉴럴 네트워크(Neural Network)로 모형화하여 기계설비 상태를 감시하는 방법을 제시한다. 또한 다단계 모델링 분석을 통하여 신호를 예측하고 설비고장 원인을 분류하며, 다른 모형과의 비교를 통하여 효율성 평가와 최적 단계수를 결정하였다. 온라인 학습 알고리즘은 recursive least squares와 clustering 방법을 이용한다.

• Bulletin of the Korean Institute for Industrial Safety
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• v.2 no.1
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• pp.1-5
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• 2002

국제표준화기구(International Standards Organization : ISO)는 현재 전 세계적인 관련분야의 전문가의 참여 하에 상태감시 및 진단 분야의 규격을 개발하고 있다. 본고에서는 기계진동 및 충격분야의 기술위원회(Technical Committee : TC)인 TC108 산하의 부분위원회(Subcommittee : SC) 5에서 수행중인 기계의 상태감시 및 진단에 관련된 제정작업의 활동현황 전반에 관해 개략적으로 설명한다.(중략)

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.9
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• pp.767-773
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• 2018

In many cases, modern aircraft are equipped with data acquisition system which checks the structural integrity of the aircraft. The analysis of the vibration data collected with the system is generally performed in dependence on a skilled expert who is familiar with aircraft design. Therefore, it is difficult to provide a representative and objective defect identification standard for general users. In this paper, we shows that it is possible to identify the type of maneuvers and faults by using the Principal Component Analysis(PCA) method in the vast vibration data collected during aircraft operation without using the existing aircraft design analysis. We classified the ROK Army aircraft vibration data for maneuvers and faults types, and applied the PCA to the classified data. Our result shows that it is possible to develop an objective maneuver/fault identification method without design analysis for general users.

• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.2 s.2
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• pp.63-74
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• 2001

In this paper the feasibility of Nondestructive Damage Detection (NDD) in large structures is demonstrated via simulating vibration monitoring of such structures. The theory of NDD for truss type structures is formulated. To examine the feasibility of the theory, a finite element model of a 3-D truss structure, which consists of sixteen bays and includes 246 elements, is developed to simulate damage. Four damage cases are simulated numerically and the cases range from the structure being damaged in one location to the structure being damaged in three locations. For the given modal parameters, this study reveals very good results for small amounts of damage as well as large damage.