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Computer Systems And Methods For Performing Root Cause Analysis And Building A Predictive Model For Rare Event Occurrences In Plant-Wide Operations

机译:在整个工厂范围内执行根本原因分析并为罕见事件发生建立预测模型的计算机系统和方法

摘要

Computer-based methods and systems perform root cause analysis with the construction of a probabilistic graph model (PGM) that explains the, e.g., negative, event dynamics of a processing plant, demonstrates precursor profiles for real-time monitoring, and provides probabilistic prediction of plant event occurrence based on real-time data. The methods and systems establish causal relationships between processing events in the upstream and resulting events in the downstream sensor data. The methods and systems provide early warnings for online process monitoring in order to prevent undesired events. The methods and systems successfully combine historical time series data with PGM analysis for operational diagnosis and prevention in order to identify the root cause of one or more events in the midst of multitude of continuously occurring events.
机译:基于计算机的方法和系统通过建立概率图模型(PGM)来执行根本原因分析,该模型解释加工厂的负面事件动态,演示用于实时监控的前体概况,并提供概率预测。基于实时数据的工厂事件发生。该方法和系统在上游的处理事件与下游的传感器数据中的结果事件之间建立因果关系。所述方法和系统为在线过程监控提供预警,以防止不期望的事件。该方法和系统成功地将历史时间序列数据与PGM分析相结合,以进行操作诊断和预防,从而在众多连续发生的事件中识别一个或多个事件的根本原因。

著录项

  • 公开/公告号US2019318288A1

    专利类型

  • 公开/公告日2019-10-17

    原文格式PDF

  • 申请/专利权人 ASPEN TECHNOLOGY INC.;

    申请/专利号US201716310904

  • 申请日2017-07-06

  • 分类号G06Q10/06;G06F11/07;G06F11/34;G06N7;G06N20;G06K9/62;

  • 国家 US

  • 入库时间 2022-08-21 12:12:38

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