• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1993년도 제18회 학술대회 초록집
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• pp.77-84
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• 1993

Systems with journal bearings generally operate in large scale and under severe loading conditions such as steam generator turbines and internal combustion engines, in contrast to the machineries using rolling element bearings. Failure of the bearings in these machineries can result in the system breakdown. To avoid the time consuming repair and considerable economic loss, the detection of incipient failure in journal bearings becomes very important. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. It has been known that the intervention of foreign materials, insufficient lubrication and misassembly etc. are principal factors to cause bearing failure and distress. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. The results showed that acoustic emission could be an effective tool to detect the incipient failure in journal bearings.

• 항공우주시스템공학회지
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• 제3권2호
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• pp.31-38
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• 2009

COMS On-board FDIR(Failure Detection, Isolation and Recovery) functions are implemented on the on-board software to satisfy the autonomy and failure tolerance requirements. This paper presents concepts of COMS Failure Management with hierarchical layers and addresses the characteristics of the FDIR layer from low level to high level. It is aimed at giving the reader the understanding how the COMS FDIR was designed and how works. It first recalls what are the system level applicable requirements, which are based on the COMS mission requirements. Then it describes the philosophy and structure of the FDIR and subsequently breaks it down into the several FDIR layers. It could be used as an important and useful reference of the information to design and develop an automatic FDIR mechanism in the future.

• 시스템엔지니어링학술지
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• 제18권1호
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• pp.46-57
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• 2022

In this paper, we proposed the DFMEA Implementation Method for safety design of Weapon System. First, we presented the process for DFMEA. And then, the case analysis of OOO missile was performed in accordance with the process presented. After defining the system requirements of OOO missile, failure definition scoring criteria was set. In order to clarify the definition of failure, the failure was classified into safety, reliability, maintainability and others. After performing the function analysis, the relationship matrix analysis was performed to identify the failure mode according to the function without omission. After clarifying the failure classification, mode of failure, cause of failure and effect were analyzed to calculate the severity, occurrence and detection values. After the action priority was judged, the recommended action according to the failure classification was identified for the determined action priority. The results of this study can be used as a relevant basis for the design reflection and resource re-allocation of stakeholders.

• 응용통계연구
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• 제26권1호
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• pp.111-118
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• 2013

이 논문에서는 고장감지장치(FDE)가 시스템 가용도에 미치는 영향을 연구한다. 주시스템(MS) 수리 도중에 고장이 발생한 FDE를 수리하기 위한 새로운 수리 정책을 고려한다. 이 논문의 주요 목적은 MS의 가용도를 계산하고 비교하는 데에 있다.

• 품질경영학회지
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• 제42권1호
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• pp.43-61
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• 2014

Purpose: This study identifies preventive measures for VOC management by analyzing the causes and effects of factors that contribute to high risk service failure using FMEA on KORAIL VOC data. Methods: Two research methods were used. First, a Risk Priority Number (RPN) was assigned to each KORAIL VOC based on Failure Mode and Effect Analysis (FMEA). Second, multiple regression analysis was run with RPN factors that include severity, occurrence, and detection as the independent variables and customer dissatisfaction as the dependent variable. Results: Multiple regression analysis showed that RPN factors including severity, occurrence, and detection had significantly positive relationship with customer dissatisfaction. Based on these results, an FMEA was performed on VOC categories with high RPN for railroad stations including platform, ticketing, ticket verification, parking, and escalator, and VOC categories with high RPN for trains including entrance doors, cafes, air quality, announcement, and ticket verification. Conclusion: This study has practical implications to service failure management. A priority order using FMEA was established for the list of customer dissatisfactions that should be addressed to actively manage service failure, and strategies for tackling this priority list are offered.

• 대한조선학회논문집
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• 제30권4호
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• pp.8-16
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• 1993

자동항법장치(Auto-Pilot System)에 의한 방향제어는 방위계측센서에 의해 계측된 위치 정보와 선미조타장치를 바탕으로 이루어진다. 대부분의 제어시스템들은 센서 잡음을 제외하고는 고장이 없는 계측장비와 고장없는 actuator를 가정하여 상태추정 빛 제어알고리듬을 구현하고 있다. 그러나 실제 상황에서는 이러한 가정이 위험한 경우가 많다. 즉, 방위 계측장비가 고장인 난 경우, 이 잘못된 위치 정보에 기초한 제어기능은 심각한 안전상의 문제까지도 야기시킬 수 있는 것이다. 본 연구에서는 개선된 위치정보처리 방법을 포함시킨 제어시스템을 Auto-Pilot 시스템에 적용하여 보았다. 그 방법으로 센서 고장 진단 및 actuator 고장 진단용 BJDF(Beard-Jones Detection Filter)를 설계하여 그 기능을 파악하였고 일반적인 상태변수추정기와의 차이점을 보였다. 특히 센서의 Bias Error의 경우 상태변수 확장기법을 이용하여 actuator 고장진단의 모형으로 모형화 할 수 있음을 보였다. 이로 인하여 센서 고장의 경우 2차원 평면에 국한된 residual이 일정 방향의 residual로 되므로 고장진단이 용이함을 알 수 있었다.

• Advances in aircraft and spacecraft science
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• 제7권1호
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• pp.1-17
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• 2020

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.

• Journal of Hydrospace Technology
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• 제1권1호
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• pp.75-88
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• 1995

Auto-Pilot System uses heading angle information via the position sensor and the rudder device to control the ship's direction. Most of the control logics are composed of the state estimation and control algorithms assuming that the measurement device and the actuator have no fault except the measurement noise. But such asumptions could bring the danger in real situation. For example, if the heading angle measuring device is out of order the control action based on those false position information could bring serious safety problem. In this study, the control system including improved method for processing the position information is applied to the Auto-Pilot System. To show the difference between general state estimator and F.D.F., BJDFs for the sensor and the actuator failure detection are designed and the performance are tested. And it is shown that bias error in sensor could be detected by state-augmented estimator. So the residual confined in the 2-dimension in the presence of the sensor failure could be unidirectional in output space and bias sensor error is much easier to be detected.

• 한국전기전자재료학회논문지
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• 제29권2호
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• pp.125-130
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• 2016

In this paper, various heat dissipation designs for a rail anchoring failure detection module were investigated by a thermal flow analysis. For the detection module with the heat dissipation design on the overall housing surface, an average temperature inside the module was lowered by $25^{\circ}C$ when compared to no heat dissipation design. In addition, an internal heat-flow blocking layer and an heat conduction layer inserted between the LED module and housing case were effective in reducing the temperature in the rail anchoring failure detection, which has a limited space for installation and little air flow. Especially, the temperature near LED module decreased below $55^{\circ}C$ when the optimal heat dissipation design was applied.

• 설비공학논문집
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• 제20권7호
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• pp.508-516
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• 2008

Fault detection and diagnosis(FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. An experimental study has been performed on fault detection and diagnosis method for a water chiller. Bayes classifier, which is one of classical pattern classifiers, is adopted in deciding whether fault occurred or not. Failure modes in this study include refrigerant leakage, decrease in mass flow rate of the chilled water and cooling water, and sensor error of the cooling water inlet temperature. It is possible to detect and diagnose faults in this study by adopting FDD algorithm using only four parameters(compressor outlet temperature, chilled water inlet temperature, cooling water outlet temperature and compressor power consumption). Refrigerant leakage failure is detected at 20% of refrigerant leakage. When mass flow rate of the chilled and cooling water decrease more than 8% or 12%, FDD algorithm can detect the faults. The deviation of temperature sensor over $0.6^{\circ}C$ can be detected as fault.