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Evaluating equipment reliability function and mean residual life based on proportional hazard model and semi-Markov process

机译:基于比例风险模型和半马尔可夫过程的设备可靠性函数和平均剩余寿命评估

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Based on Monte Carlo technique, a novel method is proposed to evaluate the reliability function (RF) and the mean residual life (MRL) of a power system component suffering from degradation. It is assumed that both the age and the health condition can affect failure rate. The Cox's proportional hazard model (PHM) is used to customize the hazard rate of component with both age and health information. PHM consists of two parts: baseline function and link function. The baseline function represents the aging process and the link function represents the influence of covariant, such as the health condition. The health condition is divided into и-stages which confirms to a semi-Markov process. Based on the Monte Carlo technique, an algorithm is developed to find out the RF and MRL of a new or aging piece of equipment. We calculate the RF and MRL in the two cases respectively: (1) a new component and (2) an aging component survived until t. The case study shows that the proposed method can reflect the influence of both age and health condition on RF and MRL reasonably.
机译:基于蒙特卡洛技术,提出了一种新的方法来评估遭受退化的电力系统组件的可靠性函数(RF)和平均剩余寿命(MRL)。假定年龄和健康状况都会影响故障率。 Cox的比例危害模型(PHM)用于根据年龄和健康信息自定义组件的危害率。 PHM由两部分组成:基线功能和链接功能。基线函数代表老化过程,链接函数代表协变量的影响,例如健康状况。健康状况分为и阶段,这证实了半马尔可夫过程。基于蒙特卡洛技术,开发了一种算法来找出新设备或老化设备的RF和MRL。我们分别计算这两种情况下的RF和MRL:(1)一个新分量,(2)一个老化分量存活到t。案例研究表明,该方法可以合理地反映年龄和健康状况对射频和最大残留限量的影响。

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