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Machinery condition monitoring system selection - A multi-objective decision approach using GA

机译:机械状态监测系统选择-使用遗传算法的多目标决策方法

摘要

In this paper, a framework for Condition Based Maintenance (CBM) of large engineering systems has been suggested to address the need to optimize the characteristics of both the condition monitoring system and the plant that is being maintained at a macro level. CBM for large engineering systems has been modeled using Markov process. The issues which are critical to CBM, namely, predictability, detectability as well as implications of availability and cost have been considered in the framework to provide effective decision support. The application of the framework has been demonstrated using a numerical example. The trade offs between the Pareto optimal solutions of various objectives have been studied and the effects of variation of the maintenance objective function values with detectability and predictability have been brought out.
机译:在本文中,已提出大型工程系统的基于状态的维护(CBM)框架,以解决优化状态监测系统和宏观维护工厂的特性的需求。大型工程系统的CBM已使用Markov过程建模。在框架中考虑了对煤层气至关重要的问题,即可预测性,可检测性以及可用性和成本的影响,以提供有效的决策支持。框架的应用已通过数值示例进行了演示。研究了各种目标的帕累托最优解之间的权衡,并提出了维护目标函数值随可检测性和可预测性而变化的影响。

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