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MODEL-PLANT MISMATCH DETECTION WITH SUPPORT VECTOR MACHINE FOR CROSS-DIRECTIONAL PROCESS BEHAVIOR MONITORING

机译:支持向量机的模型工厂故障检测,用于横向过程行为监控

摘要

A method includes obtaining (402) operating data associated with operation of a cross-directional industrial process controlled by at least one model-based process controller (106, 204). The method also includes, during a training period (502a, 502b), performing (406) closed-loop model identification with a first portion of the operating data to identify multiple sets of first spatial and temporal models. The method further includes identifying (408) clusters (604) associated with parameter values of the first spatial and temporal models. The method also includes, during a testing period (504a, 504b), performing (410) closed-loop model identification with a second portion of the operating data to identify second spatial and temporal models. The method further includes determining (412) whether at least one parameter value of at least one of the second spatial and temporal models falls outside at least one of the clusters. In addition, the method includes, in response to such a determination (414), detecting that a mismatch exists between actual and modeled behaviors of the industrial process.
机译:一种方法包括获得(402)与由至少一个基于模型的过程控制器(106、204)控制的横向工业过程的操作相关联的操作数据。该方法还包括在训练时段(502a,502b)期间,对操作数据的第一部分执行(406)闭环模型识别,以识别多组第一空间和时间模型。该方法还包括识别(408)与第一空间和时间模型的参数值相关联的集群(604)。该方法还包括在测试时段(504a,504b)期间,对操作数据的第二部分执行(410)闭环模型识别,以识别第二空间和时间模型。该方法还包括确定(412)第二空间和时间模型中的至少一个的至少一个参数值是否落在至少一个集群之外。另外,该方法包括响应于这种确定(414),检测在工业过程的实际行为与建模行为之间存在不匹配。

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