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    • 61. 发明公开
    • CORRELATION AND ANNOTATION OF TIME SERIES DATA SEQUENCES TO EXTRACTED OR EXISTING DISCRETE DATA
    • 时间序列数据序列提取或存在离散数据的相关性和注释
    • EP3055747A1
    • 2016-08-17
    • EP13785986.4
    • 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.
    • 用于通过将时间序列数据与其他类型的非时间序列数据关联来预测事件的系统可以包括处理器,该处理器被配置为接收包括从被配置为测量被监视的组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先导指标。 处理器从时间序列数据中提取任何识别的感兴趣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,计算置信水平以表示事件发生的概率,从而量化所提取事件的数据与已知历史模式之间的关系。
    • 63. 发明公开
    • Methods for determining multiple simultaneous fault conditions
    • Verfahren zur Bestimmung mehrerer simultanerFehlerzustände
    • EP2854031A1
    • 2015-04-01
    • EP14183633.8
    • 2014-09-04
    • Honeywell International Inc.
    • Bell, Douglas AllenFelke, Tim
    • G06F11/00G05B23/02G06F11/07
    • G06F11/08G05B23/02G05B23/0229G06F11/008G06F11/0706G06F11/079
    • The present application relates to a method for determining multiple simultaneous fault conditions on complex systems. The method comprises receiving symptoms of a complex system from monitors. When some of the symptoms suggest the existence of multiple simultaneous fault conditions, then the method creates a symptom signature, creates one or more failure mode signatures, and creates an error code for each failure mode signature in regard to the symptom signature. Each failure mode signature is associated with only one failure mode. A Hamming distance is determined for each failure mode indicated as possibly causing the original fault condition. Each failure mode with the minimum Hamming distance and same Hamming Code are grouped together as being one of the multiple simultaneous fault conditions. All remaining failure modes with other Hamming distances are then assigned into one of the simultaneous fault conditions.
    • 本申请涉及一种用于在复杂系统上确定多个同时故障状况的方法。 该方法包括从监视器接收复杂系统的症状。 当某些症状表明存在多个同时发生的故障情况时,该方法将创建一个症状签名,创建一个或多个故障模式签名,并针对症状签名为每个故障模式签名创建错误代码。 每个故障模式签名仅与一个故障模式相关联。 对于可能导致原始故障状态的每个故障模式确定汉明距离。 具有最小汉明距离和相同汉明码的每个故障模式被分组在一起作为多个同时故障条件之一。 所有其他汉明距离的剩余故障模式都被分配到同时故障条件之一。
    • 64. 发明公开
    • System monitoring
    • Systemüberwachung
    • EP2642362A2
    • 2013-09-25
    • EP13159609.0
    • 2013-03-15
    • GE Aviation Systems Limited
    • Callan, Robert
    • G05B23/02
    • G06F11/3055G05B23/021G05B23/0229G06F11/3058G06F11/3447
    • Monitoring of a system (10) is disclosed, in particular to identify the cause of conditions outside expected operating conditions. The output of one or more sensors (11,12,13) associated with a system (10) is monitored (40) and data from the one or more sensors is arranged (50) as a plurality of modes (101,102) with each mode being defined by a different condition in which the system may operate, such as different ambient conditions, variations in the physical configuration of the system and different operating conditions. Faulty conditions are identified (60) by monitored data being outside one of the plurality of modes. The use of a plurality of modes enables operation of the system to be defined and tracked more precisely so that operation of the system outside expected parameters may be detected more precisely and false alarms may be reduced. At least one of the modes may be established to indicate a particular failure of the system. This failure mode may have a likely cause of the failure associated with it such that diagnosis and repair may be facilitated quickly and easily.
    • 公开了对系统(10)的监视,特别是用于识别超出预期操作条件的条件的原因。 监视与系统(10)相关联的一个或多个传感器(11,12,13)的输出(40),并且来自一个或多个传感器的数据被布置(50)为多个模式(101,102),每个模式 由系统可操作的不同条件(例如不同的环境条件,系统的物理配置的变化和不同的操作条件)来定义。 由多个模式之一的监视数据识别故障条件(60)。 使用多种模式能够更精确地定义和跟踪系统的操作,使得可以更准确地检测出系统外部期望参数的操作,并且可以减少假警报。 可以建立至少一种模式来指示系统的特定故障。 该故障模式可能具有与其相关联的故障的可能原因,使得可以快速且容易地促进诊断和修复。