• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.6
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• pp.43-52
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• 2022

Operational reliability of the single-use turbo engine for guided weapons must be guaranteed even after long-term storage. Rolling element bearings have a great influence on the operational reliability of the turbo engine, however changes in micro dimensions of bearings by an oxide layers on rolling elements and raceways may cause failures after long-term storage. In this study, changes in dimensions of bearings were measured and roughness of rolling elements was used for estimating the storage life. Storage life estimation was performed via two kinds of methods, Weibayes method and random sample generation method. The results of two methods were compared and their characteristics were analyzed. This study will contribute to establish an efficient maintenance schedule for the single-use turbo engine.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.7
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• pp.565-572
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• 2021

In this study, a study on the performance and aging of explosive bolts stored for a long time among pyrotechnic mechanical devices(PMD) used as separation devices in the defense field is conducted. For this, explosive bolts that had been installed in the weapon system for about 10 years are secured. Performance and life extension test procedures are established based on the AIAA Standard and MIL-STD. Before performance evaluation, non-functional tests are performed to check whether external changes or failures occurred. Next, circuit inspection and X-ray tests are conducted to check the failure in internal circuits and structures. After that, performance test is carried out to confirm the operation of the samples that passed the non-functional test. Through this test, separation of bolt and separation time are measured, and some samples are tested after a high temperature storage test to confirm the remaining life and the possibility of extension. Finally, the remaining life and reliability are predicted based on the results of the test and the Arrhenius model to identify remaining shelf life and reliability depend on time.

• 한국가스학회:학술대회논문집
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• 2005.10a
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• pp.167-174
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• 2005

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.130-132
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• 2020

배터리 시스템은 어플리케이션의 대영화에 따른 데이터 저장공간 문제 및 연속적인 배터리 신뢰성 문제 해결을 위한 건전성 예측 및 관리기술 접목에 관한 문제에 직면해 있으며, 이러한 문제 해결을 위해서는 배터리 시스템 신호를 통해 추출 가능한 건전성 지표 수립이 중요하다. 본 논문은 건전성 지표를 물리적, 간접적 지표로써 정의하고, 사이클 노화 데이터를 통해 건전성 지표로써의 성능을 검증하였다.

• Journal of the Korean Institute of Gas
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• v.24 no.6
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• pp.91-97
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• 2020

Lithium-ion batteries (LIBs) have a longer lifespan, higher energy density, and lower self-discharge rates than other batteries, therefore, they are preferred as an Energy Storage System (ESS). However, during years 2017-2019, 28 ESS fire accidents occurred in Korea, and accurate capacity estimation of LIB is essential to ensure safety and reliability during operations. In this study, data-driven modeling that predicts capacity changes according to the charging cycle of LIB was conducted, and developed models were compared their performance for the selection of the optimal machine learning model, which includes the Decision Tree, Ensemble Learning Method, Support Vector Regression, and Gaussian Process Regression (GPR). For model training, lithium battery test data provided by NASA was used, and GPR showed the best prediction performance. Based on this study, we will develop an enhanced LIB capacity prediction and remaining useful life estimation model through additional data training, and improve the performance of anomaly detection and monitoring during operations, enabling safe and stable ESS operations.