Principal component analysis based fault classification
    11.
    发明授权
    Principal component analysis based fault classification 有权
    基于主成分分析的故障分类

    公开(公告)号:US08041539B2

    公开(公告)日:2011-10-18

    申请号:US12187975

    申请日:2008-08-07

    IPC分类号: G06F17/18

    摘要: Principle Component Analysis (PCA) is used to model a process, and clustering techniques are used to group excursions representative of events based on sensor residuals of the PCA model. The PCA model is trained on normal data, and then run on historical data that includes both normal data, and data that contains events. Bad actor data for the events is identified by excursions in Q (residual error) and T2 (unusual variance) statistics from the normal model, resulting in a temporal sequence of bad actor vectors. Clusters of bad actor patterns that resemble one another are formed and then associated with events.

    摘要翻译: 原理分量分析(PCA)用于对过程进行建模,采用聚类技术对基于PCA模型的传感器残差代表事件的偏移进行分组。 PCA模型对正常数据进行培训,然后运行包含正常数据的历史数据和包含事件的数据。 事件的不良演员数据通过来自正常模型的Q(残差)和T2(异常方差)统计的偏移来识别,导致不良演员向量的时间序列。 形成彼此类似的不良演员模式的群集,然后与事件相关联。

    BATCH PROCESS MONITORING USING LOCAL MULTIVARIATE TRAJECTORIES
    12.
    发明申请
    BATCH PROCESS MONITORING USING LOCAL MULTIVARIATE TRAJECTORIES 有权
    使用当地多种类型的TRAJECTORIES进行批处理过程监控

    公开(公告)号:US20090143873A1

    公开(公告)日:2009-06-04

    申请号:US11948785

    申请日:2007-11-30

    IPC分类号: G05B13/04

    CPC分类号: G05B17/02

    摘要: A system and method include determining a state of a batch process. Historical segments are retrieved from a historical database of trajectories of the batch process as a function of the state of the batch process. A model is created as a function of the retrieved historical segments. The model is used to provide state information about the batch process and may then be discarded.

    摘要翻译: 系统和方法包括确定批处理的状态。 作为批处理过程的状态的函数,从批处理的轨迹的历史数据库检索历史段。 根据检索的历史段创建模型。 该模型用于提供关于批处理的状态信息,然后可以被丢弃。