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Reliability Modelling of Multiple Repairable Units

机译:多个可修复单元的可靠性建模

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This paper proposes a model selection framework for analysing the failure data of multiple repairable units when they are working in different operational and environmental conditions. The paper provides an approach for splitting the non-homogeneous failure data set into homogeneous groups, based on their failure patterns and statistical trend tests. In addition, when the population includes units with an inadequate amount of failure data, the analysts tend to exclude those units from the analysis. A procedure is presented for modelling the reliability of a multiple repairable units under the influence of such a group to prevent parameter estimation error. We illustrate the implementation of the proposed model by applying it on 12 frequency converters in the Swedish railway system. The results of the case study show that the reliability model of multiple repairable units within a large fleet may consist of a mixture of different stochastic models, that is, the homogeneous Poisson process/renewal process, trend renewal process, non-homogeneous Poisson process and branching Poisson processes. Therefore, relying only on a single model to represent the behaviour of the whole fleet may not be valid and may lead to wrong parameter estimation. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:本文提出了一个模型选择框架,用于分析多个可维修单元在不同运行和环境条件下工作时的故障数据。本文提供了一种基于非均匀故障数据集的故障模式和统计趋势检验将其分解为同类组的方法。此外,当总体中包含失效数据量不足的单位时,分析人员倾向于从分析中排除这些单位。提出了一种用于在这样的组的影响下对多个可修复单元的可靠性进行建模的过程,以防止参数估计误差。我们通过将其应用于瑞典铁路系统中的12个变频器来说明该模型的实现。案例研究结果表明,大型机队中多个可维修单元的可靠性模型可能由不同随机模型的混合物组成,即均匀泊松过程/更新过程,趋势更新过程,非均匀泊松过程和泊松过程分支。因此,仅依靠单个模型来表示整个机队的行为可能无效,并可能导致错误的参数估计。版权所有(c)2015 John Wiley&Sons,Ltd.

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