公开(公告)号：US20100010985A1

公开(公告)日：2010-01-14

申请号：US12320538

申请日：2009-01-28

申请人： Andrew Wong ,  Chung Lam Li

发明人： Andrew Wong ,  Chung Lam Li

IPC分类号： G06F17/30

CPC分类号： G06F17/30539 ,  G06F17/30598

摘要： In its broad aspect, the invention provides a method for analyzing relationships among patterns within a data set having a set of samples and associated attribute values defining each attribute of each said sample. The method comprises receiving at an input at least two patterns; defining a data cluster within the data set for each of said at least two patterns, each defined data cluster having samples with attribute values associated with a corresponding pattern of said at least two patterns; grouping at least some of the samples of each defined data cluster with one another to generate a resultant data cluster; and calculating a variation between the attribute values of a first set of samples and the attribute values of a second set of samples within said resultant data cluster, the attribute values of the first set of samples and the second set of samples corresponding to the same attribute.

摘要翻译： 在其广泛的方面，本发明提供了一种用于分析具有一组样本的数据集中的模式之间的关系的方法，以及定义每个所述样本的每个属性的相关属性值。 该方法包括在输入端处接收至少两个图案; 为所述至少两个图案中的每一个定义数据集内的数据簇，每个定义的数据集具有具有与所述至少两个图案的对应图案相关联的属性值的样本; 将每个定义的数据集群的至少一些样本彼此分组以生成结果数据集群; 以及计算第一组样本的属性值与所述结果数据簇中第二组样本的属性值之间的变化，第一组样本的属性值和对应于相同属性的第二组样本 。

公开(公告)号：US07996404B2

公开(公告)日：2011-08-09

申请号：US12320538

申请日：2009-01-28

申请人： Andrew Wong ,  Chung Lam Li

发明人： Andrew Wong ,  Chung Lam Li

IPC分类号： G06F17/30

CPC分类号： G06F17/30539 ,  G06F17/30598

摘要： In its broad aspect, the invention provides a method for analyzing relationships among patterns within a data set having a set of samples and associated attribute values defining each attribute of each said sample. The method comprises receiving at an input at least two patterns; defining a data cluster within the data set for each of said at least two patterns, each defined data cluster having samples with attribute values associated with a corresponding pattern of said at least two patterns; grouping at least some of the samples of each defined data cluster with one another to generate a resultant data cluster; and calculating a variation between the attribute values of a first set of samples and the attribute values of a second set of samples within said resultant data cluster, the attribute values of the first set of samples and the second set of samples corresponding to the same attribute.

摘要翻译： 在其广泛的方面，本发明提供了一种用于分析具有一组样本的数据集中的模式之间的关系的方法，以及定义每个所述样本的每个属性的相关属性值。 该方法包括在输入端处接收至少两个图案; 为所述至少两个图案中的每一个定义数据集内的数据簇，每个定义的数据集具有具有与所述至少两个图案的对应图案相关联的属性值的样本; 将每个定义的数据集群的至少一些样本彼此分组以生成结果数据集群; 以及计算第一组样本的属性值与所述结果数据簇中第二组样本的属性值之间的变化，第一组样本的属性值和对应于相同属性的第二组样本 。

公开(公告)号：US20110320388A1

公开(公告)日：2011-12-29

申请号：US13141944

申请日：2009-12-23

申请人： Andrew Wong ,  Chung Lam Li

发明人： Andrew Wong ,  Chung Lam Li

IPC分类号： G06F15/18

CPC分类号： G05B23/0232 ,  G05B23/0278 ,  G06K9/6256 ,  G06K9/6269 ,  G06N5/025 ,  G06N7/005 ,  G06N99/005

摘要： The present invention relates to control, monitoring, and automation. The present invention more specifically relates to pattern-based intelligent control, monitoring and automation. The invention performs pattern-based monitoring. It collects signal data from one or more signals. The signal data define signal data streams. It then transforms each of the signal data streams into trends. It also discovers patterns based on the trends within each signal data stream and/or across the signal data streams. The patterns are optionally used for diagnostics and root cause analysis, online plant monitoring and operation control, plant optimization, and other environments where a causal link or correlation may exist between related inputs, states and/or outputs.

摘要翻译： 本发明涉及控制，监控和自动化。 本发明更具体地涉及基于模式的智能控制，监控和自动化。 本发明执行基于模式的监视。 它从一个或多个信号收集信号数据。 信号数据定义信号数据流。 然后将每个信号数据流转换成趋势。 它还基于每个信号数据流和/或跨信号数据流的趋势发现模式。 这些模式可选地用于诊断和根本原因分析，在线工厂监控和操作控制，工厂优化以及其他在相关输入，状态和/或输出之间存在因果链接或相关性的环境。

公开(公告)号：US09423793B2

公开(公告)日：2016-08-23

申请号：US13141944

申请日：2009-12-23

申请人： Andrew Wong ,  Chung Lam Li

发明人： Andrew Wong ,  Chung Lam Li

IPC分类号： G06F15/18 ,  G05B23/02 ,  G06N7/00 ,  G06N5/02 ,  G06K9/62 ,  G06N99/00

CPC分类号： G05B23/0232 ,  G05B23/0278 ,  G06K9/6256 ,  G06K9/6269 ,  G06N5/025 ,  G06N7/005 ,  G06N99/005

摘要： The present invention relates to control, monitoring, and automation. The present invention more specifically relates to pattern-based intelligent control, monitoring and automation. The invention performs pattern-based monitoring. It collects signal data from one or more signals. The signal data define signal data streams. It then transforms each of the signal data streams into trends. It also discovers patterns based on the trends within each signal data stream and/or across the signal data streams. The patterns are optionally used for diagnostics and root cause analysis, online plant monitoring and operation control, plant optimization, and other environments where a causal link or correlation may exist between related inputs, states and/or outputs.

摘要翻译： 本发明涉及控制，监控和自动化。 本发明更具体地涉及基于模式的智能控制，监控和自动化。 本发明执行基于模式的监视。 它从一个或多个信号收集信号数据。 信号数据定义信号数据流。 然后将每个信号数据流转换成趋势。 它还基于每个信号数据流和/或跨信号数据流的趋势发现模式。 这些模式可选地用于诊断和根本原因分析，在线工厂监控和操作控制，工厂优化以及其他在相关输入，状态和/或输出之间存在因果链接或相关性的环境。