可修系统故障过程的时变尺度参数威布尔模型

R. Jiang
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引用次数: 3

摘要

寿命分布模型通常不适用于可修系统的连续故障间隔时间(TBF)建模,因为TBF通常不是独立且相同分布的。传统的可修系统故障过程建模方法侧重于将平均累积函数(MCF)拟合到幂律模型等参数模型上。然而,拟合模型不能直接提供给定系统年龄或故障事件下下一次故障的时间分布。为了解决这一问题,本文提出了一种具有恒定形状参数和时变尺度参数的威布尔模型来建模可修系统的tbf。它包括威布尔分布作为它的特例。提出了三种具体的尺度参数模型。该模型适用于系统的MTBF可能是单调的或浴缸形的,并且有界的情况。这种模型可以看作是威布尔过程模型。这些模型的潜在应用包括制造缺陷发生过程的建模和维护有效性的评估。包括三个现实世界的例子来说明这些模型的适当性和有用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Weibull Model with Time-Varying Scale Parameter for Modeling Failure Processes of Repairable Systems
A lifetime distribution model is usually inappropriate for modeling the times between successive failures (TBF) of a repairable system since the TBFs are generally not independent and identically distributed. Traditional methods for modeling the failure process of repairable systems focus on fitting the mean cumulative function (MCF) to a parametric model such as the power-law model. However, the fitted model does not directly provide the distribution of the time to the next failure at a given system age or failure event. To address this issue, we propose a Weibull model with constant shape parameter and time-varying scale parameter for modeling TBFs of a repairable system in this paper. It includes the Weibull distribution as its special case. Three specific parametric models for the scale parameter are developed. The models are suitable for the situations where the system's MTBF can be monotonic or bathtub-shaped, and bounded. Such a model can be viewed as a Weibull process model. Potential applications of the models include modeling manufacturing defect occurrence processes and evaluating the effectiveness of maintenance. Three real-world examples are included to illustrate the appropriateness and usefulness of these models.
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