首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science >An improved fuzzy programming model with an L–R fuzzy number for filter management strategies in fluid power systems under uncertainty
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An improved fuzzy programming model with an L–R fuzzy number for filter management strategies in fluid power systems under uncertainty

机译:不确定条件下流体动力系统滤波器管理策略的改进的带有LR模糊数的模糊规划模型

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摘要

A fuzzy non-linear programming model is developed for the assessment of filter allocation and replacement strategies in fluid power systems (FPSs) under uncertainty. It can not only handle uncertainties expressed as L–R fuzzy numbers, but also enhance the system robustness by transforming the fuzzy inequalities into inclusive constraints. In modelling formulation, theory of contamination wear is introduced to reflect the interactions between system performance and system contamination level. The developed method has been applied to the planning of filter allocation and replacement for an FPS with a bypass filtration system, and a piecewise linearization approach is proposed for solving model non-linearities. Three different contaminant ingression rates are examined based on a number of filter-installation scenarios. The generated solutions can be used for providing guidance to decision makers to identify better contamination control plans for achieving a minimized system cost and system-failure risk.
机译:建立了模糊非线性规划模型,用于评估不确定性下流体动力系统(FPS)中的过滤器分配和更换策略。它不仅可以处理用L–R模糊数表示的不确定性,而且可以通过将模糊不等式转换为包容性约束来增强系统的鲁棒性。在建模公式中,引入了污染磨损理论以反映系统性能和系统污染水平之间的相互作用。所开发的方法已被应用到带有旁路过滤系统的FPS的过滤器分配和更换计划中,并提出了一种用于解决模型非线性问题的分段线性化方法。根据许多过滤器安装方案,检查了三种不同的污染物进入率。生成的解决方案可用于为决策者提供指导,以确定更好的污染控制计划,以实现最小的系统成本和系统故障风险。

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