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    • 2. 发明申请
    • CORRELATION AND ANNOTATION OF TIME SERIES DATA SEQUENCES TO EXTRACTED OR EXISTING DISCRETE DATA
    • 时间序列数据序列与提取的或现有的离散数据的关联和归纳
    • WO2015053774A1
    • 2015-04-16
    • PCT/US2013/064209
    • 2013-10-10
    • GE INTELLIGENT PLATFORMS, INC.
    • AGGOUR, Kareem, SherifBOWMAN, Ward, LinnscottCOURTNEY, Brian, ScottINTERRANTE, John, A.MATHUR, SunilWILLIAMS, Jenny Marie, Weisenberg
    • G05B23/02
    • G06N7/005G05B23/0229G06F17/30516G06N99/005
    • A system for predicting events by associating time series data with other types of non-time series data can include a processor configured to receive a data stream including time series data transmitted from a sensor configured to measure an operating parameter of a component being monitored. The processor identifies sequences of interest in the time series data having predictive value. The processor compares the real-time data stream to a set of known historical patterns that act as effective leading indicators of different alarms and events. The processor extracts any identified sequences of interest from the time series data as an extracted event. The processor quantifies the relationship between the data of the extracted event and the known historical pattern by calculating a confidence level to denote a probability of occurrence of the event by comparing how closely the new time series data matches the data patterns associated with known events.
    • 通过将时间序列数据与其他类型的非时间序列数据相关联来预测事件的系统可以包括处理器,其被配置为接收包括从被配置成测量被监视的部件的操作参数的传感器发送的时间序列数据的数据流。 处理器识别具有预测值的时间序列数据中的感兴趣序列。 处理器将实时数据流与一组已知的历史模式进行比较,这些历史模式充当不同警报和事件的有效领先指示器。 处理器从时间序列数据中提取任何识别的感兴趣的序列作为提取的事件。 处理器通过比较新时间序列数据与已知事件相关联的数据模式的匹配程度,通过计算置信水平来表示事件发生的概率来量化提取事件的数据与已知历史模式之间的关系。