• Journal of KSNVE
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• v.14 no.1
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• pp.18-23
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• 2004

균열 현상은 모든 필터에서 발생하였다. 1997년 9월 원심 압축기 B에서 발생한 지나친 진동현상으로 여러 필터 중 한 필터가 부서져 임펠러 흡입부로 빨려 들어갔다. 1997년 10월 기동중에 선회실속 문제가 임펠러에서 발생하였고, 이 원인은 임펠러 eye가 부분적으로 막혔기 때문이었다. 압축기 입구와 출구의 전체 유량과 압력 상태는 정상이었기 때문에 어떠한 서지현상도 anti-surge 시스템에 의해서 감지되지 않았다. 고장상태를 진단함으로써 압축기의 재가동을 방지하여 필터들이 부서졌다는 것을 확인하게 되었다. 이번 기계 점검과정을 통하여 원격진단의 중요성을 확인하였으며, 이에 회사는 원격서비스(remote service) 계약을 체결하여 현재 원격 진단 서비스 점검이 계약 기간에 따라 정기적으로 이루어지고 있다. 이와 같이 기계에 대한 정기적인 점검을 실시하는 목적은 기계의 결함이나 고장문제를 조기에 발견함으로써 중대한 고장으로의 진행을 사전에 예방하거나 또는 최소화하는데 있다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2378-2387
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• 1998

This thesis proposes a design algorithm of an efficient space response compactor for Built-In Self-Testing of VLSI circuits. The proposed design algorithm of space compactors can be applied independently from the structure of Circuit Cnder Test. There are high hardware overhead cost in conventional space response compactors and the fault coverage is reduced by aliasing which maps faulty circuit's response to fault-free one. However, the proposed method designs space response compactors with reduced hardware overheads and does not reduce the fault coverage comparing to conventional method. Also, the proposed method can be extended to general N -input logic gate and design the most efficient space response L'Ompactors according to the characteristies of output sequence from CUT. The prolxlsed design algorithm is implemented by C language on a SUN SPARC Workstation, and some experiment results of the simulation applied to ISCAS'85 benchmark circuits with pseudo random patterns generated bv LFSR( Linear Feedback Shift Register) show the efficiency and validity of the proposed design algorithm.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.221-221
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• 2023

1969년에 발간된 API521 1st edition에서는 Flare Load 저감용으로 적용되는 HIPS (High Integrity Protection System)는 모두 Pressure Safety Valve의 고장확률보다 낮은 SIL 3 (Safety Integrity Level)등급을 적용할 것을 요구하고 있다. Flare Stack 저감용 HIPS는 주로 압축기 출력압력상승, Reboiler Steam 과다주입, 전력공급중단냉각펌프고장 등에 의한 Flare 발생을 예방하기 위한 기능을 가진 SIF (Safety Instrumented Function)로 구성된다. 하지만 2007년도 발간된 API521 5th edition에서는 LOPA (Layer Of Protection Analysis) 분석을 통해 Target SIL을 도출하는 것으로 요구사항을 변경했다. 이에 따라 이번 연구에서는 Flare Load에 가장 큰 영향을 미치는 시나리오 중 대표적인 시나리오를 대상으로 HAZOP(Hazard and Operability Study)과 LOPA분석을 실시해서 Target SIL이 어떻게 도출되는지를 연구했다. Flare Stack에서 Flare를 발생시키는 대표적인 시나리오들에 대해 LOPA분석을 실시한 결과 압축기 출력압력상승은 SIL 2, Reboiler Steam 과다주입은 SIL 3, 전력공급중단은 SIL 0, 냉각펌프고장은 SIL 0로 모두가 SIL 3 가 나오지는 않았다. SIF 설계 시 Target SIL을 만족시키는 것도 중요하지만 운전 시 SIL 등급이 계속 유지되게 하지 위해 인적오류, 시스템적 고장, 하드웨어고장 등에 의해 SIF 기능불능화가 되는 것을 예방하기 위한 기능안전관리시스템 (FSMS)를 적용하는 것도 중요하다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.681-684
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• 2023

우리나라의 수소연료전지 차량의 점유율이 매년 증가하고 있으나, 수소충전소 설비의 잦은 중단으로 수소연료전지 차량 운전자들이 제때 차량을 충전하지 못하는 불편이 발생하고 있다. 본 논문에서는 수소충전소 설비 중 Diaphragm을 사용하는 압축기의 이상 패턴을 탐지하는 Ensemble 모델을 통해 수소충전소에서 2023년 1월 1일부터 2023년 6월 28일 동안 수집된 데이터를 분석하였으며, 해당 기간 동안 발생했던 고장에 대해 2일전부터 이상 패턴이 10,000 이상 탐지되는 결과를 얻었다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.127-134
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• 2021

In this study, an anomaly detection (AD) algorithm was implemented to detect the failure of a marine air compressor. A lab-scale experiment was designed to produce fault datasets (time-series electric current measurements) for 10 failure modes of the air compressor. The results demonstrated that the temporal pattern of the datasets showed periodicity with a different period, depending on the failure mode. An AD model with a convolutional autoencoder was developed and trained based on a normal operation dataset. The reconstruction error was used as the threshold for AD. The reconstruction error was noted to be dependent on the AD model and hyperparameter tuning. The AD model was applied to the synthetic dataset, which comprised both normal and abnormal conditions of the air compressor for validation. The AD model exhibited good detection performance on anomalies showing periodicity but poor performance on anomalies resulting from subtle load changes in the motor.

• Proceedings of the SAREK Conference
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• 2005.06a
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• pp.163-163
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• 2005

• Transactions of the Korean hydrogen and new energy society
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• v.26 no.2
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• pp.192-198
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• 2015

Fault Tree Analysis to predict the lifetime in the design process of LNG compressor is considered. Fault Trees for P & ID of the compressor are created. Individual components that comprise the compressor are configured with the basic event. The failure rates in the PDS and OREDA are applied. As results, the system failure rate and the reliability over time are obtained. Further, the power transmission and the shaft seal system is confirmed to confidentially importantly contribute to the overall lifetime of the system. These techniques will help to improve the reliability of design of large scale machinery such as a plant.

• Journal of Korean Society of Steel Construction
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• v.13 no.3
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• pp.223-232
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• 2001

Column tests subjected to compressive loading were carried out for the estimation of compression buckling strength of steel plate SM570 in beam-column member under high axial load. It was found that the maximum strength of column member was determined by local buckling when satisfied with a limit of width-to-thickness ratio in current steel structure design specifications, but decreased suddenly by local buckling before the maximum strength in case of not satisfying with that ratio. Also, the compression buckling strength of SM570 plate was higher than the design specification value of 4$4.1tonf/cm^2$.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

• Proceedings of the SAREK Conference
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• 2004.11a
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• pp.70-70
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• 2004