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Estimating residual life distribution from fractile curves of a condition variable

机译:估算来自条件变量的韧度曲线的剩余生命分布

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In a condition-based maintenance setting, a challenging issue is to determine the distribution of residual life. In this paper we propose a non-parametric approach to estimate the residual life distribution. The proposed approach starts with several empirical fractile curves of a condition variable. The curves are fitted to power-law models using a weighted least square method (with large weights being assigned to the recent observations), and the times to failure are extrapolated from the fitted power-law models. In such a way, the empirical residual life distribution is obtained. The main advantages of the proposed approach include: (a) it does not need to make assumptions about the degradation process and the distribution family of residual life; (b) the fitted power-law models can reflect recent trend; and (c) the empirical residual life distribution provides more information about the behavior of residual life since a number of fractile curves are used. These advantages make the prediction more accurate. A real-world example is included to illustrate the appropriateness and usefulness of the approach.
机译:在基于条件的维护环境中,具有挑战性的问题是确定残留寿命的分布。在本文中,我们提出了一种非参数化方法来估计残留的生命分布。所提出的方法从条件变量的若干经验骨折曲线开始。使用加权最小二乘法(将近期观察分配的大量大量)安装在电力 - 法律模型上,并且失败的时间是从装配的电力法模型推断。以这种方式,获得了经验残留的生命分布。拟议方法的主要优势包括:(a)它不需要对劣化过程和分布家庭进行残留寿命的假设; (b)合适的幂律模型可以反映近期趋势; (c)经验剩余寿命分布提供了有关剩余寿命行为的更多信息,因为使用了许多抗毛头曲线。这些优点使预测更准确。包括一个真实的示例,以说明这种方法的适当性和有用性。

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