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首页> 外文会议>6th International Conference on Reliability Maintainability amp; Safety >Reliability Assessment For Complex System with Small Samples Based on Performance Degradation Data
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Reliability Assessment For Complex System with Small Samples Based on Performance Degradation Data

机译：基于性能退化数据的小样本复杂系统可靠性评估

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摘要

Degradation is a phenomenon where certain measurements of quality characteristics deteriorate over time. For the high reliability and expensive products in aerospace fields, life tests result in few or no failures. In such cases, it is difficult to assess reliability with traditional life tests that record only time to failure. If failure is defined in terms of a specified level of degradation, a degradation model defines a particular time-to-failure distribution. In this article, a linear stochastic degradation process model is proposed. Then the model is applied to the assessment of the reliability of some liquid propellant rocket engine. The parameters of the model is estimated with ML-II(the second maximum likelihood) method based on Bayes theory. The advantage of the presented methodology is that the times to failure are not directly observed but the degradation that can be accurately measured. Consequently, the test time can be significantly shorter than if the times to failure are recorded. At last a numerical example is given to illustrate the efficiency of this model.
机译：降级是某些质量特性度量随时间降低的现象。对于航空航天领域中的高可靠性和昂贵的产品，寿命测试导致很少或没有失败。在这种情况下，仅记录故障时间的传统寿命测试很难评估可靠性。如果根据指定的退化级别定义了故障，则退化模型将定义特定的故障发生时间分布。本文提出了一种线性随机降解过程模型。然后将该模型应用于某些液体火箭发动机可靠性的评估。基于贝叶斯理论，采用ML-II（第二最大似然法）估计模型的参数。所提出的方法的优点是失效时间不是直接观察到的，而是可以精确测量的退化程度。因此，与记录故障时间相比，测试时间可以大大缩短。最后，通过数值例子说明了该模型的有效性。

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