• 제목/요약/키워드: Performance Degradation Model

검색결과 540건 처리시간 0.032초

터보엔진 구성품용 스프링의 저장 신뢰성 평가 (Storage Reliability Assessment of Springs for Turbo Engine Components)

  • 장무성;이충성;박종원;김유일;김선제
    • 한국추진공학회지
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    • 제23권4호
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    • pp.42-49
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    • 2019
  • 본 연구에서는 가속열화시험을 이용하여 터보엔진 구성품용 스프링의 저장 신뢰도를 예측하는 방법을 제시한다. 스프링의 신뢰성 평가 절차를 먼저 수립한 후, 스프링의 성능열화특성은 스프링 상수로 선정한다. 또한 스프링 상수를 노화시키는 가속 스트레스 인자는 온도로 결정한다. 본 연구에서는 터보엔진에 사용되는 스프링에 대해서 3가지 온도 조건에서 시험을 실시하며, 각각의 온도 조건에서 스프링의 노화 상태를 확인하기 위해 주기적으로 스프링 상수를 측정한다. 스프링의 고장시간은 열화모델을 이용하여 예측하며, 최종적으로 고장시간과 가속모델을 이용하여 사용조건에서 스프링의 저장 수명을 예측한다.

Analysis on Co-channel Interference of Human Body Communication Supporting IEEE 802.15.6 BAN Standard

  • Hwang, Jung-Hwan;Kang, Tae-Wook;Kim, Youn-Tae;Park, Seong-Ook
    • ETRI Journal
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    • 제37권3호
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    • pp.439-449
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    • 2015
  • Human body communication (HBC) is being recognized as a new communication technology for mobile and wearable devices in a body area network (BAN). This paper presents co-channel interference experienced by HBC supporting the physical layer in the IEEE 802.15.6 BAN standard. To analyze the co-channel interference, a co-channel interference model is introduced, and space-domain and time-domain parameters representing an interference environment are generated using the co-channel interference model. A new signal-to-interference ratio (SIR) parameter depending on the peak amplitudes of the data signals causing co-channel interference is defined; co-channel interference can be easily analyzed and modelled using the newly defined SIR. The BER degradation model derived using the co-channel interference model and SIR in this paper can be effectively used to estimate the performance.

광대역 무선통신 채널 환경에서 OFDM 시스템의 성능개선 (Performance Improvement of OFDM Systems in Broadband Wireless Communication Channel Environments)

  • 강희조
    • 한국항행학회논문지
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    • 제11권1호
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    • pp.37-42
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    • 2007
  • 본 논문에서는 비선택성 페이딩과 주파수 오프셋이 함께 존재하는 채널과 마이크로파 대역의 2경로 Rummer's 채널 환경에서 적응 등화기를 채용한 OFDM 시스템의 성능을 분석하였다. 주파수 비선택성 페이딩과 주파수 오프셋이 함께 존재하는 채널에서 시스템 성능 분석 결과 주파수 오프셋의 증가에 따른 성능이 급격히 열화 됨을 알 수 있다, 그리고 시스템에서 적응 등화기를 채용한 경우에는 일정 범위 내에서 성능 향상이 이루어짐을 확인할 수 있었다.

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3자유도 능동형 제진 시스템의 불확실성과 제어 (Uncertainties and control of a 3-DOF active vibration isolation system)

  • 김화수;박희재;문준희
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2006년도 추계학술대회논문집
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    • pp.925-933
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    • 2006
  • Using the physics-based model for the vibration isolation system, the model uncertainties are described. With the model including parameter perturbations, the robust controller to meet the robust performance and stability is designed through $\mu$-synthesis by DK-iteration. The order of controller is reduced by virtue of Hankel norm approximation technique to allow the efficient implementation in the real-time experimental environment without any performance degradation. The performance of the reduced $\mu$-controller is accessed in comparison with the original one. The experiments validate the superiority of the proposed control scheme against the model uncertainties and its applicability with varying payload.

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3자유도 능동형 제진 시스템의 불확실성과 제어 (Uncertainties and Control of a 3-DOF Active Vibration Isolation System)

  • 김화수;박희재;조영만;문준희
    • 한국소음진동공학회논문집
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    • 제16권12호
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    • pp.1262-1271
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    • 2006
  • Using the physics-based model for the vibration isolation system, the model uncertainties are described. With the model including parameter perturbations, the robust controller to meet the robust performance and stability is designed through $\mu$-synthesis by DK-iteration. The order of controller is reduced by virtue of Hankel norm approximation technique to allow the efficient implementation in the real-time experimental environment without any performance degradation. The performance of the reduced $\mu$-controller is accessed in comparison with the original one. The experiments validate the superiority of the proposed control scheme against the model uncertainties and its applicability with varying payload.

A Risk-based System Analysis Model for Improving the Performance of Financial Solutions

  • Lee, Jong Yun;Kim, Jong Soo;Kim, Tai Suk
    • 한국멀티미디어학회논문지
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    • 제18권11호
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    • pp.1367-1374
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    • 2015
  • In this paper, we propose a model which can prioritize the performance improvement work by analyzing the major risks and their influence, which can cause performance degradation in the system and show an example of a performance improvement using this model. In presentation-tier, as a result of log data analysis before and after the performance improvement of key processes which handle financial transactions, this model brought the CPU utilization and memory enhancement in the performance improvement work of the financial system which was carried out by applying the proposed model. It has been confirmed that the entire end-user can be accommodated. In the web-tier, the available memory increased by 200MB and we were able to improve the server restart(Recycling) that was sustained in the existing system. In the business logic-tier, we have been able to see better figures after performance improvements through the graph which analyzes the log collected with the key performance counters such as CPU%, Batch Requests/sec. In the data-tier, it has been confirmed that CPU usage and standby operation were reduced and the throughput was found to increase.

The Performance Analysis to Identify the Reuse and Assembly Impact of Temporary Equipment

  • Bae, Sung-Jae;Park, Jun-Beom;Kim, Jung-Yeol;Kim, Young-Suk;Kim, Jun-Sang;Jo, Jae-Hun
    • 국제학술발표논문집
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    • The 9th International Conference on Construction Engineering and Project Management
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    • pp.1252-1252
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    • 2022
  • Temporary work that utilizes temporary equipment (e.g., system scaffold and system pipe support) in construction work is one of the most vulnerable work from a safety perspective in South Korea. Typically, temporary equipment is reused at construction sites. The Korea Occupational Safety and Health Agency announced guidelines regarding the performance standards for reusable temporary equipment to prevent the accidental collapse of temporary facilities. Nevertheless, temporary facilities' collapse still occurs, which could be attributed to a degradation in the performance due to the reuse of temporary equipment. Therefore, this study investigated the performance of simple temporary structures assembled with new and reused equipment. To this end, an experimental module was designed based on previous research cases, and two experimental models were constructed, in which one was assembled using new equipment (Model A), and the other was built using reused equipment (Model B). To determine the performance of each model, a load test was conducted to measure the maximum load that each model could withstand. The experimental results revealed that the maximum load of Model B was 15% lower than that of Model A. This indicates that there is a meaningful performance difference between those two models. Based on this result, the authors decided to perform additional tests with more realistic models than previous ones. The new experimental module was designed to ensure compliance with the Korean design guidelines. In this presentation, the authors show details of the first tests and their results and plan for the additional test.

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A Study of Performance Monitoring and Diagnosis Method for Multivariable MPC Systems

  • Lee, Seung-Yong;Youm, Seung-Hun;Lee, Kwang-Soon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.2612-2616
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    • 2003
  • Method for performance monitoring and diagnosis of a MIMO control system has been studied aiming at application to model predictive control (MPC) for industrial processes. The performance monitoring part is designed on the basis of the traditional SPC/SQC method. To meet the underlying premise of Schwart chart observation that the observed variable should be univariate and independent, the process variables are decorrelated temporally as well as spatially before monitoring. The diagnosis part was designed to identify the root of performance degradation among the controller, process, and disturbance. For this, a method to estimate the model-error and disturbance signal has been devised. The proposed methods were evaluated through numerical examples.

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충전 특성과 어텐션 기반 LSTM을 활용한 개선된 리튬이온 배터리 SOH 예측 모델 (Improved SOH Prediction Model for Lithium-ion Battery Using Charging Characteristics and Attention-Based LSTM)

  • 류한일;이상훈;최덕재;박혁로
    • 스마트미디어저널
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    • 제12권11호
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    • pp.103-112
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    • 2023
  • 최근 리튬이온 배터리 사용이 늘어남에 따라 배터리 화재 및 사고 예방의 필요성이 대두되고 있다. 사고 예방을 위해서는 배터리 SOH(State of Health)를 예측하여 열화가 많이 진행된 배터리의 교체 시기를 확인하는 것이 필요하다. 본 논문에서는 배터리의 충전 과정에서 얻을 수 있는 최대 전압 도달 시간, 전류 변화 시간, 최대 온도 도달 시간, IC(Incremental Capacity) 등 4가지 배터리 열화 특성과 어텐션 메커니즘을 이용한 장단기 메모리(Long Short Term Memory, LSTM)를 사용하여 배터리의 열화 상태를 예측하는 모델을 제안한다. NASA에서 제공하는 배터리 데이터 세트를 사용해 제안하는 모델의 성능을 측정한 결과 일반적인 LSTM 모델을 사용하는 경우보다 예측성능의 개선을 확인할 수 있었고, 특히 배터리 교체 주기에 가까운 SOH 90-70% 구간에서 더 우수한 성능을 보였다.

경년열화를 고려한 전단벽 구조물의 기계학습 기반 지진응답 예측모델 개발 (Development of Machine Learning Based Seismic Response Prediction Model for Shear Wall Structure considering Aging Deteriorations)

  • 김현수;김유경;이소연;장준수
    • 한국공간구조학회논문집
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    • 제24권2호
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    • pp.83-90
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    • 2024
  • Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.