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A signed directed graph-based systematic framework for steady-state malfunction diagnosis inside control loops

机译:基于有向图的有向图系统框架,用于控制回路内的稳态故障诊断

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Although signed directed graphs (SDG) have been widely used for modeling control loops, due to lack of adequate understanding of SDG-based steady-state process modeling, special and cumbersome methods are used to analyze control loops. In this paper, we discuss a unified SDG model for control loops, in which both disturbances (sensor bias, etc.) as well as structural faults (sensor failure, controller failure, etc.) can be easily modeled under steady-state conditions. Various fault scenarios such as external disturbances, sensor bias, controller failure, etc. have been thoroughly analyzed. A new algorithm for steady-state fault diagnosis using the SDG model for the steady-state system, that uses a combination of forward- and backward-reasoning, is proposed. Three case studies are presented to show the utility of the steady-state SDG model for fault diagnosis. A tank-level control system is used as the first case study. The second case study deals with fault diagnosis of a multi-stream-control led CSTR. The third case study deals with fault/failure diagnosis in a process flowsheet containing a CSTR with one control loop and a flash vaporizer with three control loops. (c) 2005 Elsevier Ltd. All rights reserved.
机译:尽管有符号有向图(SDG)已广泛用于控制回路的建模,但是由于对基于SDG的稳态过程建模缺乏足够的了解,因此使用了特殊且繁琐的方法来分析控制回路。在本文中,我们讨论了用于控制回路的统一SDG模型,在该模型中,可以轻松地在稳态条件下对干扰(传感器偏置等)以及结构性故障(传感器故障,控制器故障等)进行建模。各种故障情况,例如外部干扰,传感器偏置,控制器故障等,都已得到彻底分析。提出了一种使用SDG模型对稳态系统进行稳态故障诊断的算法,该算法结合了前向推理和后向推理。提出了三个案例研究,以显示稳态SDG模型在故障诊断中的实用性。坦克级控制系统被用作第一个案例研究。第二个案例研究涉及多流控制LED CSTR的故障诊断。第三个案例研究在一个过程流程图中处理故障/故障诊断,该流程图包含具有一个控制回路的CSTR和具有三个控制回路的闪蒸器。 (c)2005 Elsevier Ltd.保留所有权利。

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