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RePofe: Reliability physics of failure estimation based on stochastic performance degradation for the momentum wheel

机译:RePofe:动量轮基于随机性能退化的故障估计的可靠性物理

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摘要

Momentum Wheel (MW) is the critical component for long life satellites. The reliability test, prediction and estimation of MW is of enormous challenges because of the special characteristics of small sample, long life and high test cost. Since it is impossible to obtain a large sample of failure data given limited money and time, the traditional statistical methods usually fail to resolve the reliability assessment problem of MW, and the efficient estimation of its reliability level can hardly be acquired. To address this problem, a novel reliability estimation framework in terms of physics of failure is advanced in this article, which is essentially based on the relationship between the MWs physics performance and its failure mechanisms. According to the actual physics of failure test and engineering analysis, a stochastic threshold Gauss-Brown process model is established to describe MW's failure process, and then a detailed parameter estimation method for the model is put forward. Finally, the effectiveness of our model is demonstrated through numerical computation based on the test data.
机译:动量轮(MW)是长寿命卫星的关键组件。 MW的可靠性测试,预测和估计面临着巨大的挑战,因为它具有样本量小,寿命长和测试成本高的特点。由于有限的金钱和时间不可能获得大量的故障数据样本,因此传统的统计方法通常无法解决MW的可靠性评估问题,并且难以获得对其可靠性水平的有效估计。为了解决这个问题,本文提出了一种新的基于失效物理的可靠性估计框架,该框架主要基于MWs物理性能与其失效机制之间的关系。根据故障测试和工程分析的实际物理原理,建立了随机阈值高斯-布朗过程模型来描述兆瓦的故障过程,并提出了详细的模型参数估计方法。最后,通过基于测试数据的数值计算来证明我们模型的有效性。

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