• 한국정밀공학회지
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• 제12권1호
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• pp.15-21
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• 1995

Automatic monitoring of cutting process is one of the most important technologies for increasing the stability and the reliability of unmanned manufacturing system. In this study, the methods which use laser displacement signals and banded energy method are proposed to monitor chatter vibration in the turning process. From this method, the monitoring system of the chatter vibration was developed and investigated its practical possibility. As a result, it is shown by experiments that the chatter vibration can be detected accurately, and it can be widely used in most turning processes.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1998년도 추계학술발표회요약집
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• pp.88-88
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• 1998

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2019년도 춘계학술논문요약집
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• pp.161-162
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• 2019

• Smart Structures and Systems
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• 제10권6호
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• pp.517-546
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• 2012

In this paper, vibration-based methods to monitor damage in foundation-structure interface of harbor caisson structure are presented. The following approaches are implemented to achieve the objective. Firstly, vibration-based damage monitoring methods utilizing a variety of vibration features are selected for harbor caisson structure. Autoregressive (AR) model for time-series analysis and power spectral density (PSD) for frequency-domain analysis are selected to detect the change in the caisson structure. Also, the changes in modal parameters such as natural frequency and mode shape are examined for damage monitoring in the structure. Secondly, the feasibility of damage monitoring methods is experimentally examined on an un-submerged lab-scaled mono-caisson. Finally, numerical analysis of un-submerged mono-caisson, submerged mono-caisson and un-submerged interlocked multiple-caissons are carried out to examine the effect of boundary-dependent parameters on the damage monitoring of harbor caisson structures.

• 한국소음진동공학회논문집
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• 제26권6_spc호
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• pp.651-659
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• 2016

Condition monitoring (CM) encounters a large data problem due to sensors that measure vibration data with a continuous, and sometimes, high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate the efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer samples compared to traditional sampling methods. For the experiments a built-in rotating system was used and all data were compressively sampled to obtain compressed data. Optimal signal features were then selected without the reconstruction process and were used to detect and classify damage. The experimental results show that the proposed method could improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• 반도체디스플레이기술학회지
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• 제23권2호
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• pp.129-134
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• 2024

This study aims to talk about the necessity of solving the PFC gas emission problem raised by the recent development of the semiconductor industry and the remote plasma source method monitoring system used in the semiconductor industry. The 'monitoring system' means that the researchers applied machine learning to the existing monitoring technology and modeled it. In the process of this study, Residual Gas Analyzer monitoring technology and linear regression model were used. Through this model, the researchers identified emissions of at least 12700mg CO2 to 75800mg CO2 with values ranging from ion current 0.6A to 1.7A, and expect that the 'monitoring system' will contribute to the effective calculation of greenhouse gas emissions in the semiconductor industry in the future.

• 풍력에너지저널
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• 제15권2호
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• pp.23-36
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• 2024

In this study, a health monitoring system was developed for the two most vulnerable parts of a wind tower support structure: the connection between steel towers (L-Flange) and the concrete foundation-steel tower connection. To select assessment parameters for health monitoring, detailed FEM analysis was conducted using the ABAQUS program. Additionally, a testbed was established near the Jeju Woljeongri wind turbine farm to evaluate the applicability of measurement data by installing sensors. Through computational analysis and relevant criteria review, we defined limits for measurement parameters by vulnerable section. We categorized the structural safety evaluation into four stages: normal, caution, warning, and danger, and selected management criteria for each stage. From this, an algorithm to evaluate safety was developed, and a visualized monitoring platform based on the established critical parts monitoring system was developed.

• 한국해안·해양공학회논문집
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• 제26권1호
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• pp.1-8
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• 2014

본 연구에서는 우리나라 동해안에 설치된 해안침식대책공법 중 잠제시설에 대한 현장모니터링을 수행하고 그 효용성을 확인하고자 하였다. 해안침식대책시설은 3년의 계획과 3년의 시공으로 총 6년간에 걸쳐 완공되었으며, 계획단계에 있어서의 수치모형실험결과와 관측결과 등에 대해서는 Kim et al.(2008, 2011)에 의해 소개되어 있다. 본 연구에서는 현장관측을 통해 잠제시설 설치 이후의 해빈폭 증가 현상을 확인하였고 해빈폭이 늘어난 원인을 잠제의 기본적인 성능인 파랑제어효과에 의한 것임을 알 수 있었다. 대상해역의 파랑관측은 잠제 시설 전면과 후면 즉 내해측과 외해측에서 수행하였다. 외해의 관측지점(수심 H = 16.5m)과 내측지점(H = 3.7 m)에 메모리형 파고계를 설치하여 파고관측결과를 도출하고 잠제시설의 파랑저감효과는 제체(잠제시설)를 투과하는 파랑의 전달율(Kt)로 분석하였다. 현장관측자료를 분석한 결과, 내습하는 파랑을 저감시켜 해안침식을 방지하기 위해 설치된 잠제의 파랑저감효과는 약 60%를 나타내고 있는 것으로 확인되었다.

• 비파괴검사학회지
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• 제36권1호
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• pp.45-52
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• 2016

고로는 제철소에서 철을 만들어 내는 핵심설비 중 하나로 고온고압 환경에서 냉각과 팽창으로 인한 철피의 손상이 노출되어 있어 대형사고에 대한 발생 가능성이 높아 중점관리가 필요하다. 본 연구에서는 음향방출법을 이용한 대형구조물 안전진단 시스템에 대한 평가를 수행하였다. 특히, 철피 크랙의 성장은 큰 에너지를 수반하게 되어, 음향방출 에너지 파라미터의 급격한 증가로 심각한 손상을 예측하였다. 이러한 결과를 바탕으로 고로의 정비시기를 앞당겨 확인한 결과 실제 크랙을 UT와 병행하여 확인하였다. 본 연구에서는 음향방출법을 이용한 대형 구조물인 철피균열의 심각도에 대한 평가기준을 마련하여 구조물 조기 결함진단 시스템의 활용으로 유용할 것으로 기대된다.

• Tribology and Lubricants
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• 제24권3호
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• pp.111-121
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• 2008

An integrated in-line oil monitoring detector assigned for continuous in situ monitoring multiple parameters of oil performance for predicting economically optimal oil change intervals and equipment condition control is presented in this study. The detector estimates oil deterioration based on the information about chemical degradation, total contamination, water content of oil and oil temperature. The oil oxidation is estimated by "chromatic ratio", total contamination is measured by the changes in optical intensity of oil in three optical wavebands ("Red", "Green" and "Blue") and water content is evaluated as Relative Saturation of oil by water. The detector is able to monitor oils with low light absorption (hydraulic, transformer, turbine, compressor and etc. oils) as well as oils with rather high light absorption in visible waveband (diesel and etc. oils). In a case study that the detector is applied to a diesel engine oil, it is found that the detector provides good results on oil chemical degradation as well as soot concentration.