• Proceedings of the KSR Conference
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• 2009.05a
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• pp.495-504
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• 2009

As the Reliability Centered Maintenance(RCM) is being studied, maintenance tasks can be performed effectively through the Risk Priority Number(RPN) evaluation about the components in the system. The RPN is usually calculated through arithmetical operations of three values, Severity, Occurrence, and Detection for each facility. This RPN provides information that includes risk level of the facility and the priority order of maintenance tasks for facility. However, if there is no sufficient historical failure data, it is difficult to calculate the RPN. In this case, historical failure data from other sources can be used and apply this data to korean railway system. In this paper, it is proposed that a new methodology to model the failure rate as a fuzzy membership function. This method is based on failure data from other sources by means of the fuzzy theory and the expert opinion system. And considering assessment tendency of each expert, distortions that happened when the failure rate of facilities is estimated were minimized. This results determine Occurrence values of facilities. Taking advantage of this result., the RPN can be calculated with Severity and Detection of facilities by using the fuzzy operation. The proposed method is applied the rail-way power substation.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.55-58
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• 2001

본 논문에서는 해석적인 모델에 기초한 고장 검출 기법의 하나인 fault detection filter를 적용한 고장 검출 알고리듬을 개발하고 이를 적용하여 고장검출 필터의 유효성을 보이고자 한다. Fault detection filter는 특수한 형태의 observer로써 특정한 고장의 발생시 잔차가 출력 공간에서 일정한 방향을 유지함으로써 고장 개소의 판별이 가능하다. 이에 본 논문에서는 fault detection filter에 기초한 고장 감지 시스템을 적용하기 위한 다이나믹 시스템 모델링과 고장감지 시스템의 설계과정 및 이를 적용 모의시험 결과를 수록하였다. 결과를 통하여 fault detection filter가 갖는 방향성에 대한 sensitivity 효과를 고장 감지 목적에 유효하게 적용할 수 있음을 보였다.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.761-769
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• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• Nuclear Engineering and Technology
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• v.42 no.1
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• pp.125-130
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• 2010

Sipping measurements were implemented at the Open Pool Australian Light water reactor (OPAL) to test for failure in reactor fuel elements. Fission product released by the fuel element into the pool water was measured using both High Purity Germanium (HPGe) detection via samples and a NaI(Tl) detection in-situ with the sipping device. Results from two fuel elements are presented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.757-758
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• 2009

• Journal of the Society of Naval Architects of Korea
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• v.59 no.4
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• pp.192-199
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• 2022

With the advent of autonomous ships, it is emerging as one of the very important issues not only to operate with a minimum crew or unmanned ships, but also to secure the safety of ships to prevent marine accidents. On-site inspection of the hull is mainly performed by the inspector's visual inspection, and video information is recorded using a small camera if necessary. However, due to the shortage of inspection personnel, time and space constraints, and the pandemic situation, the necessity of introducing an automated inspection system using artificial intelligence and remote inspection is becoming more important. Furthermore, research on hardware and software that enables the automated inspection system to operate normally even under the harsh environmental conditions of a ship is absolutely necessary. For automated inspection systems, it is important to review artificial intelligence technologies and equipment that can perform a variety of hull failure detection and classification. To address this, it is important to classify the hull failure. Based on various guidelines and expert opinions, we divided them into 6 types(Crack, Corrosion, Pitting, Deformation, Indent, Others). It was decided to apply object detection technology to cracks of hull failure. After that, YOLOv5 was decided as an artificial intelligence model suitable for survey and a common hull crack dataset was trained. Based on the performance results, it aims to present the possibility of applying artificial intelligence in the field by determining and testing the equipment required for survey.

• Composites Research
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• v.17 no.2
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• pp.28-33
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• 2004

Failure detection in a cross-ply laminated composite beam under tensile loading were performed using a fiber Bragg grating (FBG) sensor. A Passive Mach-Zehnder interferometric demodulator was proposed to enhance sensitivity and bandwidth. The proposed FBG sensor system without active device such as a phase modulator is very simple in configuration, easy to implement and enables the measurement of high-frequency vibration with low strain amplitude such as impact or failure signal. Failure signals detected by a FBG sensor had offset value corresponding to the strain shift with vibration at a maximum frequency of several hundreds of kilohertz. at the instant of transverse crack propagation in the 90 degree layer of composite beam.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.7123-7127
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• 2015

Purpose: To determine the utility of secondary circulating prostate cells for predicting early biochemical failure after radical prostatectomy for prostate cancer and compare the results with the Walz nomagram. Materials and Methods: A single centre, prospective study of men with prostate cancer treated with radical prostatectomy between 2004 and 2014 was conducted, with registration of clinical-pathological details, total serum PSA pre-surgery, Gleason score, extracapsular extension, positive surgical margins, infiltration of lymph nodes, seminal vesicles and pathological stage. Secondary circulating prostate cells were obtained using differential gel centrifugation and assessed using standard immunocytochemistry with anti-PSA. Biochemical failure was defined as a PSA >0.2ng/ml, predictive values werecalculated using the Walz nomagram and CPC detection. Results: A total of 326 men participated, with a median follow up of 5 years; 64 had biochemical failure within two years. Extracapsular extension, positive surgical margins, pathological stage, Gleason score ${\geq}8$, infiltration of seminal vesicles and lymph nodes were all associated with higher risk of biochemical failure. The discriminative value for the nomogram and circulating prostate cells was high (AUC >0.80), predictive values were higher for circulating prostate cell detection, with a negative predictive value of 99%, sensitivity of 96% and specificity of 75%. Conclusions: The nomagram had good predictive power to identify men with a high risk of biochemical failure within two years. The presence of circulating prostate cells had the same predictive power, with a higher sensitivity and negative predictive value. The presence of secondary circulating prostate cells identifies a group of men with a high risk of early biochemical failure. Those negative for secondary CPCs have a very low risk of early biochemical failure.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.47-56
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• 2008

MC(Mission Computer) performs important function in avionics system which tactic data processing, image processing and managing navigation system etc. In general, the fault of SPOF(Single Point Of Failure) in unity system can lead to failure of whole system. It can cause a failure of a mission and also can threaten to the life of the pilot. So, in this paper, we design the HA(Hight-availability) system so that dealing with the failure. And we use HA software like Heartbeat, Fake, DRBD and Bonding to manage HA system. Also we analyze the performance of HA system using the FDT(Fault Detection Time) for fast fault detection and MTTR(Mean Time To Repair) for mission continuity.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.247-256
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• 2009

In mass production industries such as steel making that have large equipment, sudden stops of production process due to machine failure can cause severe problems. To prevent such situations, machine diagnosis techniques play important roles. Many methods have been developed focusing on this subject. In this paper, we propose a method for the early detection of the failure on rotating machine, which is the most common theme in the machine failure detection field. A simplified method of calculating autocorrelation function is introduced and is utilized for ARMA model identification. Furthermore, an absolute deterioration factor such as Bicoherence is introduced. Machine diagnosis can be executed by this simplified calculation method of system parameter distance with weight. Proposed method proved to be a practical index for machine diagnosis by numerical examples.