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Finding the Source of Nonlinearity in a Process With Plant-Wide Oscillation

机译:在整个植物范围内的振荡过程中寻找非线性源

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A plant-wide oscillation in a chemical process often has an impact on product quality and running costs and there is, thus, a motivation for automated diagnosis of the source of such a disturbance. This brief describes a method of analyzing data from routine operation to locate the root cause oscillation in a dynamic system of interacting control loops and to distinguish it from propagated secondary oscillations. The novel concept is the application of a nonlinearity index that is strongest at the source. The index is large for the nonsinusoidal oscillating tune trends that are typical of the output of a control loop with a limit cycle caused by nonlinearity. It is sensitive to limit cycles caused both by equipment and by process nonlinearity. The performance of the index is studied in detail and default settings for the parameters in the algorithm are derived so that it can be applied in a large scale setting such as a refinery or petrochemical plant. Issues arising from artifacts in the nonlinearity test when applied to strongly cyclic data have been addressed to provide a robust, reliable and practical method. The technique is demonstrated with three industrial case studies.
机译:化学过程中的全厂范围的振荡通常会影响产品质量和运行成本,因此,存在着自动诊断此类干扰源的动机。本简介描述了一种分析常规操作数据的方法,以在相互作用的控制回路的动态系统中定位根本原因振荡,并将其与传播的二次振荡区分开。新概念是在源头上应用最强的非线性指标。对于非正弦振荡调谐趋势,该指数很大,该趋势是非线性引起的具有极限循环的控制回路输出的典型特征。它对设备和过程非线性造成的极限循环很敏感。对该索引的性能进行了详细研究,并推导了算法中参数的默认设置,以便可以将其应用于大规模设置,例如炼油厂或石化厂。已经解决了非线性测试应用于强循环数据时由伪影引起的问题,以提供一种可靠,实用的实用方法。通过三个工业案例研究证明了该技术。

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