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DISCRIMINATIVE HIDDEN KALMAN FILTERS FOR CLASSIFICATION OF STREAMING SENSOR DATA IN CONDITION MONITORING

机译:区分隐藏式卡尔曼滤波器,用于状态监测中的流式传感器数据分类

摘要

A method for monitoring a condition of a system or process includes acquiring sensor data from a plurality of sensors disposed within the system (S41 and S44). The acquired sensor data is streamed in real-time to a computer system (S42 and S44). A discriminative framework is applied to the streaming sensor data using the computer system (S43 and S45). The discriminative framework provides a probability value representing a probability that the sensor data is indicative of an anomaly within the system. The discriminative framework is an integration of a Kalman filter with a logistical function (S41).
机译:用于监视系统或过程的状况的方法包括从布置在系统内的多个传感器获取传感器数据(S41和S44)。所获取的传感器数据被实时地流传输到计算机系统(S42和S44)。使用计算机系统将判别框架应用于流式传感器数据(S43和S45)。判别框架提供表示传感器数据指示系统内异常的概率的概率值。判别框架是卡尔曼滤波器与逻辑函数的集成(S41)。

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