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Reliability modeling of repairable system based on a stochastic model

机译:基于随机模型的可修复系统可靠性建模

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Reliability modeling is an important part of reliability research, which has important guiding significance for evaluating system reliability index and optimizing preventive maintenance strategy. Maintenance behaviors, such as maintenance and replacement of system components, etc. have great influence on the reliability of repairable system. But the commonly used reliability distribution models ignore the repair history, which is not in conformity with the actual engineering application. In this paper, a reliability model based on failure time and maintenance effect was established by using log-linear baseline intensity function. The proposed model overcome the lack of Weibull distribution and Weibull process that only consider the change trend of failure time and ignore the importance of repair history. Then, the proposed model was a three parameter model, and the model parameter estimation was studied by using maximum likelihood method. Finally, the reliability model was applied in the reliability analysis of a repairable Numerical Control (NC) system. The validity of the proposed model and its parameter estimation method were verified. Compared with the Weibull distribution and Weibull process, the proposed model has obvious superiority, and fits the cumulative number of failure curve very well.
机译:可靠性建模是可靠性研究的重要组成部分,对于评估系统可靠性指标和优化预防性维护策略具有重要的指导意义。维护行为,例如系统组件的维护和更换等,对可修复系统的可靠性有很大影响。但是常用的可靠性分布模型忽略了维修历史,这与实际工程应用不符。本文利用对数线性基线强度函数建立了基于失效时间和维护效果的可靠性模型。该模型克服了Weibull分布和Weibull过程的不足,后者仅考虑失效时间的变化趋势而忽略了维修历史的重要性。然后,提出的模型是一个三参数模型,并使用最大似然法研究了模型参数的估计。最后,将可靠性模型应用于可修复数控系统的可靠性分析中。验证了所提模型及其参数估计方法的有效性。与威布尔分布和威布尔过程相比,该模型具有明显的优越性,并且很好地拟合了失效曲线的累积数。

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