DATA MODELING STUDIO
    1.
    发明公开
    DATA MODELING STUDIO 审中-公开
    数据建模工作室

    公开(公告)号:EP3200131A1

    公开(公告)日:2017-08-02

    申请号:EP17157505.3

    申请日:2014-03-17

    摘要: A data modeling studio provides a structured environment for graphically creating and executing models which may be configured for diagnosis, prognosis, analysis, identifying relationships, etc., within a process plant. The data modeling studio includes a configuration engine for generating user interface elements to facilitate graphical construction of a model and a runtime engine for executing data models in, for example, an offline or an on-line environment. The configuration engine includes an interface routine that generates user interface elements, a plurality of templates stored in memory that serve as the building blocks of the model and a model compiler that converts the graphical model into a data format executable by the run-time engine. The run time engine executes the model to produce the desired output and may include a retrieval routine for retrieving data corresponding to the templates from memory and a modeling routine for executing the executable model.

    摘要翻译: 数据建模工作室提供了一个结构化的环境,用于图形化地创建和执行可能配置用于过程工厂内的诊断,预测,分析,识别关系等的模型。 数据建模工作室包括用于生成用户界面元素的配置引擎,以促进模型的图形化构建以及用于在例如离线或在线环境中执行数据模型的运行时引擎。 配置引擎包括生成用户界面元素的界面例程,存储在存储器中的用作模型的构建块的多个模板以及将图形模型转换为可由运行时引擎执行的数据格式的模型编译器。 运行时引擎执行模型以产生期望的输出,并且可以包括用于从存储器检索与模板对应的数据的检索例程和用于执行可执行模型的建模例程。

    GRAPHICAL PROCESS VARIABLE TREND MONITORING, PREDICTIVE ANALYTICS AND FAULT DETECTION IN A PROCESS CONTROL SYSTEM
    3.
    发明公开
    GRAPHICAL PROCESS VARIABLE TREND MONITORING, PREDICTIVE ANALYTICS AND FAULT DETECTION IN A PROCESS CONTROL SYSTEM 审中-公开
    在过程控制系统的过程变量预测分析和故障检测图形趋势监测

    公开(公告)号:EP3156871A1

    公开(公告)日:2017-04-19

    申请号:EP16193584.6

    申请日:2016-10-12

    IPC分类号: G05B23/02

    摘要: A process control monitoring system for a process control plant uses graphic trend symbols to assist in detecting and monitoring trends of process variables within the process control plant. A graphic display application within the process control monitoring system may implement and display each graphic trend symbol to graphically indicate or encapsulate current trend and value information of a process variable within the process control plant. The graphic display application may display the graphic trend symbol in a spatially realistic location within a graphical representation of the process control plant while maintaining the hierarchical structure or each hierarchical level of the process plant. The graphic display application may also include a navigation pane and a zoom feature that enable a user to quickly drill down through tend data to obtain more information and to support problem identification and diagnosis tasks.

    摘要翻译: 用于过程控制计划的过程控制监控系统采用图形符号趋势,以帮助检测和过程控制计划中的过程变量的监测趋势。 过程控制监视系统内的图形显示应用可以实现的,并显示每个图形符号的趋势,以图形方式指示或封装过程控制计划内的过程变量的当前趋势和值的信息。 同时维持分层结构或过程工厂的每个分层等级的图形显示应用可以显示在空间现实位置的过程控制计划的图形表示内的图形符号的趋势。 图形显示应用程序因此可以包括导航窗格和缩放功能确实使用户能够快速向下钻取通过数据倾向于获得更多的信息,并支持问题识别和诊断任务。

    GRAPHICAL PROCESS VARIABLE TREND MONITORING FOR A PROCESS CONTROL SYSTEM

    公开(公告)号:EP3869287A1

    公开(公告)日:2021-08-25

    申请号:EP21167732.3

    申请日:2014-03-13

    IPC分类号: G05B23/02

    摘要: A process control monitoring system for a process control plant uses graphic trend symbols to assist in detecting and monitoring trends of process variables within the process control plant. A graphic display application within the process control monitoring system may implement and display each graphic trend symbol to graphically indicate or encapsulate current trend and value information of a process variable within the process control plant. The graphic display application may display the graphic trend symbol in a spatially realistic location within a graphical representation of the process control plant while maintaining the hierarchical structure or each hierarchical level of the process plant. The graphic display application may also include a zoom feature that enables a user to quickly drill down through tend data to obtain more information and to support problem identification and diagnosis tasks.