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A Wiener process–based remaining life prediction method for light-emitting diode driving power in rail vehicle carriage:

机译:基于维纳过程的轨道车辆车厢中发光二极管驱动功率的剩余寿命预测方法:

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Remaining life prediction is an effective way to optimize maintenance strategy and improve service life for light-emitting diode driving power in rail vehicle carriage. In this article, a Wiener process–based remaining life prediction method is proposed with the analysis of performance degradation data of light-emitting diode driving power in rail vehicle carriage. First, the temperature and humidity stress accelerated degradation tests are put forward in order to measure the output current of light-emitting diode driving power. Based on the output current, the accelerated degradation model is established. The drift and diffusion coefficients of the Wiener process are then obtained without prior information. Finally, the reliability of light-emitting diode driving power in rail vehicle carriage is assessed and the remaining lifetime is predicted after updating the degradation model parameters with Bayesian inference. The results show that the proposed method can improve the precision of assessment and red...
机译:剩余寿命预测是优化维护策略并提高轨道车辆车厢中发光二极管驱动功率使用寿命的有效方法。在本文中,通过分析轨道车辆车厢中发光二极管驱动功率的性能下降数据,提出了一种基于维纳过程的剩余寿命预测方法。首先,提出了温度和湿度应力加速退化测试,以测量发光二极管驱动功率的输出电流。基于输出电流,建立加速退化模型。然后,无需先验信息即可获得维纳过程的漂移系数和扩散系数。最后,通过贝叶斯推断更新退化模型参数,评估了轨道车辆车厢中发光二极管驱动功率的可靠性,并预测了剩余寿命。结果表明,所提方法可以提高评估的准确性和重复性。

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