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Reliability estimation for one-shot devices under cyclic accelerated life-testing

机译:循环加速寿命测试下的单次设备的可靠性估计

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摘要

A one-shot device, like an automobile airbag, is a product or an equipment that can be used only once. Better quality and longer lifetime of one-shot devices nowadays increase the cost of life test experiment under normal operating condition. Cyclic stress test, adopted in life-testing experiments by increasing stress levels to induce more failures, has been used to investigate the reliability analysis of one-shot devices based on Coffin-Manson principle. However, the Coffin-Manson model only considers temperature change in each cycle. Moreover, it assumes that the reliability is independent of the cycling frequency, which may not be a realistic assumption in practice. Birnbaum-Saunders distribution, originally developed to model fatigue failure under cyclic loading, has been used widely to model lifetime data. As the Norris-Landzberg model is proposed for modeling fatigue life due to cyclic temperature fluctuation, it is used in this work together with Birnbaum-Saunders distribution for modeling lifetimes of one-shot devices under accelerated life-tests with different cyclic temperature fluctuations. It contains the Coffin-Manson model as a special case. Inferential methods for model parameters, reliability and mean lifetime are developed in this paper. Simulation study and model discrimination are carried out to evaluate the performance of the proposed model and inferential methods. Finally, an example is presented to illustrate the model and the inferential results developed here.
机译:单次设备,如汽车安全气囊,是一种可以仅使用一次的产品或设备。如今,单次设备的更好质量和更长的一生都在正常运行条件下提高了寿命试验实验的成本。通过增加压力水平来诱导更大故障的生命测试实验中采用的循环应力测试已被用来研究基于棺材曼森原则的单击装置的可靠性分析。但是,棺材 - 曼森型号仅考虑每个周期的温度变化。此外,它假设可靠性与循环频率无关,这可能在实践中可能不是真实的假设。 Birnbaum-Saunders分布,最初用于在循环负载下模拟疲劳失效的分布,已广泛用于模拟寿命数据。由于诺里斯 - Landzberg模型提出了由于循环温度波动而建模疲劳寿命,它与Birnbaum-Saunders分布一起使用,以便在加速循环温度波动下的加速寿命测试下的一击装置的寿命。它包含棺材 - 曼森模型作为一个特殊情况。本文开发了用于模型参数,可靠性和平均寿命的推理方法。进行了仿真研究和模型鉴别,以评估所提出的模型和推理方法的性能。最后,提出了一个示例以说明这里开发的模型和推理结果。

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