最大熵模型在可替换系统可靠性中心维护方案中的应用。

O. P. Gaona, D. González-González, Marco A. Fuentes-Huerta, R. Praga-Alejo
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引用次数: 1

摘要

基于变分微积分和微分熵的方法,我们在这项工作中提出了一个非参数模型,该模型提供了RCM方案中使用的可靠性的鲁棒估计。威布尔分析首先在通常的RCM方案中的一个案例研究中提出。如果数据样本严重减少,威布尔分析将失去精度,影响RCM方案。为了解决这一限制,提出了一种最大熵方法。微分熵已被证明是一个可靠的工具,以模拟一个随机变量的响应时,减少了样本大小的信息是可用的。利用变分微积分的形式化表达了一个服从欧拉-拉格朗日方程的泛函,并在Kolmogorov公理的支持下,我们提取了一个广义的非参数概率密度。通过根据广义概率密度的一阶矩使该密度具有适当的边界条件。
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Maximum entropy model applied to Reliability Centered Maintenance scheme for replaceable systems.
Based on methodologies of variational calculus and differential entropy, we propose in this work a non-parametric model that provides a robust estimation of reliability to be used in a RCM scheme. A Weibull analysis is presented first in a case study within the usual RCM schemes. If the sample of data is severly reduced the weibull analysis lost preciscion, impacting in the RCM scheme. To solve this limitation, a maximum entropy aproach is propoused.Differential entropy has been shown as a solid tool to model the response of a random variable when reduced sample size information is available. We take advantage of the formalism of the variational calculus to express a functional that obeys the Euler-Lagrange equations and supported by the Kolmogorov axioms, we extract a generalized non-parametric probability density. By subjecting this density to appropriate boundary conditions in terms of the first moments of the generalized probability density.
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