公开(公告)号：US20080091390A1

公开(公告)日：2008-04-17

申请号：US11863588

申请日：2007-09-28

申请人： Nikola SAMARDZIJA ,  Ahmad Hamad

发明人： Nikola SAMARDZIJA ,  Ahmad Hamad

IPC分类号： G06F17/10 ,  G06F17/18

CPC分类号： G05B23/0245 ,  G05B23/021 ,  G05B23/024 ,  Y10S715/965

摘要： Methods and systems to detect transient operations from abnormal operations, and to detect abnormal operations in a coker heater, include collecting on-line process data. The collected on-line process data is generated from a plurality of process variables of the process, or coker heater. A first representation of the operation of the process, or coker heater, is generated based on a first set of the collected on-line process data generated from a first set of the process variables. The first representation is adapted to be executed to generate a first result. A second representation of the operation of the process, or coker heater, is generated based on the first result and based on a second set of the collected on-line process data generated from a second set of the process variables. The second representation is adapted to be executed to generate a prediction of data generated from the second set of the process variables. The prediction is analyzed to detect an abnormal operation or to detect whether one or more abnormal operations comprises a transient operation of the process.

摘要翻译： 用于检测异常操作的瞬态操作以及检测焦化加热器异常操作的方法和系统包括收集在线过程数据。 收集的在线过程数据是从过程或焦化加热器的多个过程变量产生的。 基于从第一组过程变量产生的收集的在线过程数据的第一组生成过程操作或焦化加热器的第一表示。 第一表示适于执行以产生第一结果。 基于第一结果并基于从第二组过程变量生成的收集的在线过程数据的第二组生成过程操作或焦化加热器的第二表示。 第二表示适于执行以产生从第二组过程变量生成的数据的预测。 分析预测以检测异常操作或检测一个或多个异常操作是否包括该过程的暂时操作。

公开(公告)号：US20080082302A1

公开(公告)日：2008-04-03

申请号：US11864529

申请日：2007-09-28

申请人： Nikola Samardzija ,  Ahmad Hamad

发明人： Nikola Samardzija ,  Ahmad Hamad

IPC分类号： G06F17/18 ,  G06F15/00 ,  G06F17/10

CPC分类号： G05B23/0245 ,  G05B23/021 ,  G05B23/024 ,  Y10S715/965

摘要： Methods and systems to detect abnormal operations in a process of a process plant include collecting on-line process data. The collected on-line process data is generated from a plurality of dependent and independent process variables of the process, such as a coker heater. A plurality of multivariate statistical models of the operation of the process are generated using corresponding sets of the process data. Each model is a measure of the operation of the process when the process is on-line at different times, and at least one model is a measure of the operation of the process when the process is on-line and operating normally. The models are executed to generate outputs corresponding to loading value metrics of a corresponding dependent process variable, and the loading value metrics are utilized to detect abnormal operations of the process.

摘要翻译： 在过程工厂的过程中检测异常操作的方法和系统包括收集在线过程数据。 收集的在线过程数据是从过程的多个依赖和独立的过程变量产生的，例如焦化加热器。 使用对应的过程数据集来生成多个过程的操作的多变量统计模型。 每个模型是过程在不同时间在线进行的过程操作的度量，当过程在线并且正常运行时，至少一个模型是对过程操作的度量。 执行模型以产生对应于相应的依赖过程变量的负载值度量的输出，并且使用负载值度量来检测过程的异常操作。