• 제목/요약/키워드: System Performance Prediction

검색결과 1,863건 처리시간 0.028초

Performance Analysis of Real-time Orbit Determination and Prediction for Navigation Message of Regional Navigation Satellite System

  • Jaeuk Park;Bu-Gyeom Kim;Changdon Kee;Donguk Kim
    • Journal of Positioning, Navigation, and Timing
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    • 제12권2호
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    • pp.167-176
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    • 2023
  • This study presents the performance analysis of real-time orbit determination and prediction for navigation message generation of Regional Navigation Satellite System (RNSS). Since the accuracy of ephemeris and clock correction in navigation message affects the positioning accuracy of the user, it is essential to construct a ground segment that can generate this information precisely when designing a new navigation satellite system. Based on a real-time architecture by an extended Kalman filter, we simulated orbit determination and prediction of RNSS satellites in order to assess the accuracy of orbit and clock prediction and signal-in-space ranging errors (SISRE). As a result of the simulation, the orbit and clock accuracy was at 0.5 m and 2 m levels for 24 hour determination and six hour prediction after the determination, respectively. From the prediction result, we verified that the SISRE of RNSS for six hour prediction was at a 1 m level.

자동결함 검출시스템에서 결함크기 측정오차로 인한 오검률의 통계적 예측 (Statistical Prediction of False Alarm Rates in Automatic Vision Inspection System)

  • 주영복;허경무;박길홈
    • 제어로봇시스템학회논문지
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    • 제15권9호
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    • pp.906-908
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    • 2009
  • AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. It is important to predict the performance of an AVI to meet customer's specification in advance. Also the prediction can indicate the level of current performance of an AVI system. In this paper, we propose a statistical method for prediction of false alarm rate regarding inconsistency of defect size measurement process. For this purpose, only simple experiments are needed to measure the defect sizes for certain number of times. The statistical features from the experiment are utilized in the prediction process. Therefore, the proposed method is swift and easy to implement and use. The experiment shows a close prediction compared to manual inspection results.

R744-R404A용 캐스케이드 냉동시스템 개발에 관한 연구(2) - 최대 성능계수에 관한 예측과 비교 - (Development of cascade refrigeration system using R744 and R404A - Prediction and comparison on maximum COP(Coefficient of Performance) -)

  • 오후규;손창효
    • Journal of Advanced Marine Engineering and Technology
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    • 제35권2호
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    • pp.189-195
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    • 2011
  • 본 논문은 R744-R404A용 캐스케이드 냉동시스템의 기초 설계자료를 제공하기 위해서 COP 예측 상관식을 제안하고 그 결과를 타 상관식과 비교하였다. 작동변수로는 R404A용 고온사이클과 R744용 저온사이클의 과냉각도와 과열도, 압축기효율, 응축과 증발온도이다. 이에 대한 주요결과를 요약하면 다음과 같다. 다중회귀 분석을 통해 R744-R404A용 캐스케이드 냉동시스템의 성능 예측식을 제안하였고, 그 결과를 타 연구자들의 상관식과 비교하였다. 그 결과 본 연구에서 제안한 성능 예측식은 타 연구자들의 상관식과 일치하지 않았다. 따라서 향후 R744-R404A용 캐스케이드 냉동시스템에 대한 추가 실험 데이터와 본 연구에서 제안한 COP 예측 상관식을 비교하여 그 신뢰성을 확보할 필요가 있다.

HCBKA를 이용한 Interval Type-2 퍼지 논리시스템 기반 예측 시스템 설계 (Prediction System Design based on An Interval Type-2 Fuzzy Logic System using HCBKA)

  • 방영근;이철희
    • 산업기술연구
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    • 제30권A호
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    • pp.111-117
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    • 2010
  • To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2 TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1 Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlationship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

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A study on multi-objective optimal design of derrick structure: Case study

  • Lee, Jae-chul;Jeong, Ji-ho;Wilson, Philip;Lee, Soon-sup;Lee, Tak-kee;Lee, Jong-Hyun;Shin, Sung-chul
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제10권6호
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    • pp.661-669
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    • 2018
  • Engineering system problems consist of multi-objective optimisation and the performance analysis is generally time consuming. To optimise the system concerning its performance, many researchers perform the optimisation using an approximation model. The Response Surface Method (RSM) is usually used to predict the system performance in many research fields, but it shows prediction errors for highly nonlinear problems. To create an appropriate metamodel for marine systems, Lee (2015) compares the prediction accuracy of the approximation model, and multi-objective optimal design framework is proposed based on a confirmed approximation model. The proposed framework is composed of three parts: definition of geometry, generation of approximation model, and optimisation. The major objective of this paper is to confirm the applicability/usability of the proposed optimal design framework and evaluate the prediction accuracy based on sensitivity analysis. We have evaluated the proposed framework applicability in derrick structure optimisation considering its structural performance.

Adaptive Compensation Method Using the Prediction Algorithm for the Doppler Frequency Shift in the LEO Mobile Satellite Communication System

  • You, Moon-Hee;Lee, Seong-Pal;Han, Young-Yearl
    • ETRI Journal
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    • 제22권4호
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    • pp.32-39
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    • 2000
  • In low earth orbit (LEO) satellite communication systems, more severe phase distortion due to Doppler shift is frequently detected in the received signal than in cases of geostationary earth orbit (GEO) satellite systems or terrestrial mobile systems. Therefore, an estimation of Doppler shift would be one of the most important factors to enhance performance of LEO satellite communication system. In this paper, a new adaptive Doppler compensation scheme using location information of a user terminal and satellite, as well as a weighting factor for the reduction of prediction error is proposed. The prediction performance of the proposed scheme is simulated in terms of the prediction accuracy and the cumulative density function of the prediction error, with considering the offset variation range of the initial input parameters in LEO satellite system. The simulation results showed that the proposed adaptive compensation algorithm has the better performance accuracy than Ali's method. From the simulation results, it is concluded the adaptive compensation algorithm is the most applicable method that can be applied to LEO satellite systems of a range of altitude between 1,000 km and 2,000 km for the general error tolerance level, M = 250 Hz.

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안전무결성 수준 및 MTTFd를 활용한 개발단계의 고성능 지상체 신뢰도 예측 방안 (Reliability Prediction of High Performance Mooring Platform in Development Stage Using Safety Integrity Level and MTTFd)

  • 이민영;김상부;배인화;강소연;곽우영;이성근;오극기;최대림
    • 한국산업융합학회 논문집
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    • 제27권3호
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    • pp.609-618
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    • 2024
  • System reliability prediction in the development stage is increasingly crucial to reliability growth management to satisfy its target reliability, since modern system usually takes a form of complex composition and various complicated functions. In most cases of development stage, however, the information available for system reliability prediction is very limited, making it difficult to predict system reliability more precisely as in the production and operating stages. In this study, a system reliability prediction process is considered when the reliability-related information such as SIL (Safety Integrity Level) and MTTFd (Mean Time to Dangerous Failure) is available in the development stage. It is suggested that when the SIL or MTTFd of a system component is known and the field operational data of similar system is given, the reliability prediction could be performed using the scaling factor for the SIL or MTTFd value of the component based on the similar system's field operational data analysis. Predicting a system reliability is then adjusted with the conversion factor reflecting the temperature condition of the environment in which the system actually operates. Finally, the case of applying the proposed system reliability prediction process to a high performance mooring platform is dealt with.

Development of the Expert Seasonal Prediction System: an Application for the Seasonal Outlook in Korea

  • Kim, WonMoo;Yeo, Sae-Rim;Kim, Yoojin
    • Asia-Pacific Journal of Atmospheric Sciences
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    • 제54권4호
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    • pp.563-573
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    • 2018
  • An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

Mean Streamline Analysis for Performance Prediction of Cross- Flow Fans

  • Kim, Jae-Won;Oh, Hyoung-Woo
    • Journal of Mechanical Science and Technology
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    • 제18권8호
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    • pp.1428-1434
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    • 2004
  • This paper presents the mean streamline analysis using the empirical loss correlations for performance prediction of cross-flow fans. Comparison of overall performance predictions with test data of a cross-flow fan system with a simplified vortex wall scroll casing and with the published experimental characteristics for a cross-flow fan has been carried out to demonstrate the accuracy of the proposed method. Predicted performance curves by the present mean streamline analysis agree well with experimental data for two different cross-flow fans over the normal operating conditions. The prediction method presented herein can be used efficiently as a tool for the preliminary design and performance analysis of general-purpose cross-flow fans.

Safety Critical 시스템의 센서 결함 허용을 위한 Kalman Hybrid Redundancy 개발 (Development of Kalman Hybrid Redundancy for Sensor Fault-Tolerant of Safety Critical System)

  • 김만호;이석;이경창
    • 제어로봇시스템학회논문지
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    • 제14권11호
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    • pp.1180-1188
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    • 2008
  • As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.