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A Novel Solution-Technique Applied to a Novel WAAS Architecture

机译:一种适用于新型WAAS架构的新型解决方案技术

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摘要

The Federal Aviation Administration has embarked on an historic task of modernizing and significantly improving the national air transportation system. One system that uses the Global Positioning System (GPS) to determine aircraft navigational information is called the Wide Area Augmentation System (WAAS). This paper describes a reliability assessment of one candidate system architecture for the WAAS. A unique aspect of this study regards the modeling and solution of a candidate system that allows a novel cold sparing scheme. The cold spare is a WAAS communications satellite that is fabricated and launched after a predetermined number of orbiting satellite failures have occurred and after some stochastic fabrication time transpires. Because these satellites are complex systems with redundant components, they exhibit an increasing failure rate with a Weibull time to failure distribution. Moreover, the cold spare satellite build-time is Weibull and upon launch is considered to be a good-as-new system with an increasing failure rate and a Weibull time to failure distribution as well. The reliability model for this system is non-Markovian because three distinct system clocks are required: the time to failure of the orbiting satellites, the build time for the cold spare, and the time to failure for the launched spare satellite. A powerful dynamic fault tree modeling notation and Monte Carlo simulation technique with importance sampling are shown to arrive at a reliability prediction for a 10 year mission.
机译:联邦航空管理局已经开始了一项历史性任务,即现代化和显着改善国家航空运输系统。一种使用全球定位系统(GPS)确定飞机导航信息的系统称为广域增强系统(WAAS)。本文描述了一种用于WAAS的候选系统架构的可靠性评估。这项研究的独特之处在于候选系统的建模和解决方案,该系统允许一种新颖的冷备用方案。冷备件是WAAS通信卫星,它在预定数量的轨道卫星发生故障之后并且经过一些随机的制造时间之后被制造和发射。由于这些卫星是具有冗余组件的复杂系统,因此它们的故障率会随着Weibull故障时间的增加而增加。此外,冷备用卫星的建造时间为Weibull,并且在发射时被认为是一种新旧系统,其故障率不断增加,而且Weibull到故障的分布时间也很长。该系统的可靠性模型是非马尔可夫模型,因为需要三个不同的系统时钟:轨道卫星发生故障的时间,冷备用的建立时间以及发射的备用卫星的故障时间。强大的动态故障树建模符号和具有重要度采样的蒙特卡洛仿真技术显示出可以完成10年任务的可靠性预测。

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  • 作者

    Bavuso, J.;

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  • 年度 1998
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