• JOURNAL OF ELECTRICAL WORLD
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• 통권282호
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• pp.67-71
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• 2000

일본, 유럽 및 미국 등의 선진국에서는 전력인프라가 거의 정비되어, 새로운 전력설비에 대한 투자보다 설비의 유지 보수$\cdot$점검비용의 비율이 더 커져가고 있다. 이러한 환경 하에 정기적인 유지보수$\cdot$점검에 요하는 비용, 사고시의 복구에 소요되는 비용 및 정전으로 인한 손실 등을 포함하여 라이프사이클 코스트의 최적화가 논의되고 있다. 유지보수$\cdot$점검에 대하여는 종래의 정기적인 유지보수(Time Based Maintenance : TBM)에서 상태대응 유지보수(Condition Based Maintenance : CBM)에로의 이행으로 비용을 삭감하려는 시도도 진전되고 있다. 이 때문에 전력설비의 상태를 파악할 수 있는 적절한 센서의 설치와 저가격의 가반형 센서의 도입도 추진되고 있다. 또한 설비의 진단장치를 차에 실은 이동진단차의 도입도 시작되고 있어, 복수의 전력소를 순회하며 효율 좋은 유지보수$\cdot$점검을 할 수 있게 되었다. EH 변전소의 무인화에 따라 정전시간 단축을 위해 사고 시에 원방복구조작이 가능한 고장점 표정장치도 도입되고 있다. 최근에는 SF${_6}$가스의 환경문제도 화제가 되어 가스를 대기 중에 방출하는 일 없이 고장구분을 표정할 수 있는 분해가스센서도 개발되었다.

• Journal of the Korean Society of Systems Engineering
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• 제18권1호
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• pp.1-13
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• 2022

The Yongin Light Rail train was manufactured by Bombardier Transportation in Canada in 2008 and is a privately invested railway line that has been operating in Yongin-si, Gyeonggi-do, since 2013. When the frequency of train failure increases due to aging, and there is a delay in the delivery period of imported parts used in the Bombardier manufactured trains, timely vehicle maintenance may not be performed due to lack of parts. To solve this problem, it is necessary to build a 'vehicle parts maintenance demand forecasting system' that analyzes the accurate and actual maintenance demand annual based on the condition of vehicle parts. The full scope of analysis in this paper analyzes failure data from various angles after opening of Yongin light rail vehicle to analyze failure patterns for each part and identify replacement cycles according to possible failures and consumption of parts. Based on this study, it is expected that Yongin Light Rail's maintenance system will change from the existing time-based replacement (TBM) concept to the condition-based maintenance (CBM) concept. It is expected that this study will improve the efficiency of the Yongin Light Rail maintenance system and increase vehicle availability. This paper is a fundamental for establishing of a system for predicting the replacement timing of vehicle parts for Yongin Light Rail. It reports the results of data analysis on some vehicle parts.

• Journal of the Korean Society for Nondestructive Testing
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• 제28권6호
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• pp.469-476
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• 2008

Condition based maintenance(CBM) for the preventive diagnosis of important equipments related to safety or accident in power plant is essential by using the suitable methods based on actual power plant conditions. To improve the reliability and accuracy of the measured value at the minute leak situation, and also to monitor continuously internal leak condition of power plant valve, the development of a diagnosis and monitoring technique using multi-measuring method should be performed urgently. This study was conducted to estimate the feasibility of multi-measuring method using three different methods such as acoustic emission(AE) method, thermal image measurement and temperature difference$({\Delta}T)$ measurement that are applicable to internal leak diagnosis for the power plant valve. From the experimental results, it was suggested that the multi-measuring method could be an effective way to precisely diagnose and evaluate internal leak situation of valve.

• Journal of the Korean Society of Propulsion Engineers
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• 제23권4호
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• pp.98-103
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• 2019

Integrity prediction of the operation equipment of naval vessels is essential to maintain the efficiency of the operation performance in urgent situations. Recently, the integrated condition assessment system(ICAS) was introduced and maintained to improve operational performance. This technology is related with ICAS, and it must be localized through extensive research. In this paper, we present the results of applying the data-driven model to the predictability methods of diesel generators, which are naval vessel operation equipment.

• Journal of the Korea Safety Management & Science
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• 제6권3호
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• pp.237-247
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• 2004

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

• Journal of Applied Reliability
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• 제18권2호
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• pp.114-121
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• 2018

Purpose: This study proposes a process for evaluating the preventive maintenance policy for a system with degradation characteristics and for calculating the appropriate preventive maintenance cycle using time- and condition-based maintenance. Methods: First, the collected data is divided into the maintenance history lifetime and degradation lifetime, and analysis datasets are extracted through preprocessing. Particle filter algorithm is used to estimate the degradation lifetime from analysis datasets and prior information is obtained using LSE. The suitability and cost of the existing preventive maintenance policy are each evaluated based on the degradation lifetime and by using a minimum repair block replacement model of time-based maintenance. Results: The process is applied to the degradation of the reverse osmosis (RO) membrane in a seawater reverse osmosis (SWRO) plant to evaluate the existing preventive maintenance policy. Conclusion: This method can be used for facilities or systems that undergo degradation, which can be evaluated in terms of cost and time. The method is expected to be used in decision-making for devising the optimal preventive maintenance policy.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2006년도 추계학술대회논문집
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• pp.411-416
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• 2006

Fault detection and diagnosis is the most important technology in condition-based maintenance(CBM) system that usually begins from collecting signatures of running machines using multiple sensors for subsequent accurate analysis. With the quick development in industry, there is an increasing requirement of selecting special sensors that are cheap, robust, and easy-installation. This paper experimentally investigated performances of four types of sensors used in induction motors faults diagnosis, which are vibration, current, voltage and flux. In addition, diagnostic effects of five popular classifiers also were evaluated. First, the raw signals from the four types of sensors are collected at the same time. Then the features are calculated from collected signals. Next, these features are classified through five classifiers using artificial intelligence techniques. Finally, conclusions are given based on the experiment results.

• Proceedings of the KIEE Conference
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.545-546
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• 2011

변전설비 고장은 대규모 정전으로 이어져 국가 산업계에 엄청난 손실을 유발할 수 있고, 컴퓨터 등 정보화 기기의 확대 보급으로 순간 정전도 허용하지 않으려는 국민들의 요구가 거세어 지고 있다. 본 논문에서는 장기사용 변전설비에 대한 고장한계점을 도출하고, CBM(Condition Based Maintenance) 관리시스템을 구축함으로써 예방진단 데이터와 고장자료를 체계화하여, 향후 설비 교체기준과 설비의 상태를 기반으로 점검을 수행하도록 토대를 마련함으로써 최소 비용으로 효과적인 고장예방과 나아가 변전설비 활용도를 높임에 그 목적이 있다.

• JOURNAL OF ELECTRICAL WORLD
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• 통권298호
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• pp.59-66
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• 2001

최근 들어 전력자유화와 규제완화의 움직임에 전력수요의 신장 정체가 겹쳐 경쟁이 격화될 것으로 예상된다. 전력유통시스템에 있어서도 코스트압박이 커져 시스템 계획과 운용$\cdot$자금 계획을 종합한 경영의 효율화를 도모하는 애셋 매니지먼트의 구상이 보다 중시되어 설비의 라이프사이클 코스트를 고려한 계획$\cdot$운용이 주목을 받고 있다. 종래의 대용량$\cdot$고신뢰도 지향에서 환경적합성도 포함하는 종합적인 운용을 고려한 변전소시스템의 구축을 목적으로 정보시스템과 기기의 통합을 도모한 인텔리전트 변전소시스템을 개발하였다. 개발항목은 다음과 같다. (1) 전력유통시스템 운용$\cdot$관리에 적합한 변전소 정보시스템의 구축 스테이션레벨, 베이레벨, 프로세스레벨에서의 네트워크 구축 (2) 고도설비계획$\cdot$보전 시스템 CBM(Condition Based Maintenance)에 대응한 기기감시시스템, 설비관리시스템 (3) 정보시스템에 적합한 전압전류센서 및 기기센서 개발 변전소내 정보의 풀디지털화에 대응 (4) 콤팩트한 기기 개발 (5) 전력시스템 운용효율화에 공헌하는 시스템 개발 기기의 스트레스를 경감하는 개폐극 위상제어기술

• Journal of Applied Reliability
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• 제3권2호
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• pp.93-101
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• 2003

Life time data analysis requires some time-to-failure data to an extent. Some life tests result in few or no failure. In such cases, it is difficult to access reliability with traditional life tests that record only time to failure. Furthermore, with short product development time, reliability tests must be conducted with severe time constraints. For some devices, it is possible to obtain degradation measurements over time, and these measurements may contain useful information about product reliability. This article describes degradation reliability analysis methods to do inferences and predictions about a failure-time distribution by using software. In addition, the possibility of extension to CBM (Condition Based Maintenance) is suggested as an example of applied degradation data analysis.