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Reliability assessment of gamma deteriorating system based on bayesian updating

机译:基于贝叶斯更新的伽马劣化系统可靠性评估

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Degradation data can provide with useful information about the reliability assessment for highly reliable products. In this paper, a method based on performance degradation data is proposed to assess reliability of high reliable long life time products. The degradation process can be described as a gamma process, and then reliability can be assessed based on analysis on failure physical mechanism. In order to adjust the degradation modeling according to the actual inspection results, a Bayesian updating method to improve the lifetime distribution is also proposed. Finally, a numerical example is given to illustrate the efficiency of the proposed method. The results presented in the case study show that the updating model can describe the degradation characteristics more accurate than the original one.
机译:劣化数据可以提供有关可靠性产品的可靠性评估的有用信息。本文提出了一种基于性能劣化数据的方法,以评估高可靠的长寿命时间产品的可靠性。降解过程可以描述为伽马过程,然后可以基于故障物理机制的分析来评估可靠性。为了根据实际检查结果调整降级建模,还提出了一种提高寿命分布的贝叶斯更新方法。最后,给出了一个数值例子来说明所提出的方法的效率。在案例研究中提出的结果表明,更新模型可以描述比原始的更准确的劣化特性。

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