一个统一设计故障检测隔离和优化维护策略的框架

P. Sadegh, J. Concha, S. Stricevic, A. Thompson, Peter James Kootsookos
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引用次数: 5

摘要

传统上,故障检测与隔离(FDI)和最优维护策略的设计是由控制界和领域专家与运筹学界分开研究的。本文的目的是提供一种统一的方法,其中维护决策是由实时FDI信号驱动的。这种方法允许系统地分析和设计外国直接投资,目的是尽量减少操作和维护的总成本。我们的方法依赖于以下步骤。首先,有关资产的信息、它们可能的故障模式(由故障模式和影响分析或从历史服务数据生成)、服务业务流程以及与固定资产相关的成本从设计人员或从业者处获取。统一建模语言(UML)被用作捕获和显示此类信息的表达方式。接下来,这些信息被用来将资产退化和维护过程表示为马尔可夫过程。最后,将资产管理问题表述为对马尔可夫过程的最优控制。我们展示了FDI的基本属性如何通过对马尔可夫过程转移概率的影响来驱动运维成本和控制问题的解决方案。我们通过一个数值例子来说明在朗肯循环设备中保持适当的制冷剂充注水平的方法
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A framework for unified design of fault detection & isolation and optimal maintenance policies
Fault detection and isolation (FDI) and design of optimal maintenance policies have been traditionally studied separately by the control community and domain experts on the one hand and the operations research community on the other. The objective of this paper is to provide a unified approach where maintenance decisions are driven by real-time FDI signals. Such an approach allows systematic analysis and design of FDI with the objective of minimizing the overall costs of operations and maintenance (O&M). Our approach relies on the following steps. First, the information about the assets, their likely failure modes (as generated by failure modes and effects analysis or from historical service data), service business processes, and costs associated with fixing the assets are captured from designers or practitioners. The Unified Modeling Language (UML) is used as an expressive way to capture and display such information. Next, this information is used to arrive at a representation of the asset degradation and maintenance process as a Markov process. Finally, the asset management problem is formulated as an optimal control over the Markov process. We show how the fundamental properties of FDI drive the O&M costs and the solution to the control problem through their impact on transition probabilities of the Markov process. We illustrate the approach by a numerical example for maintaining proper refrigerant charge levels in Rankine cycle equipment
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