公开(公告)号：US20180364655A1

公开(公告)日：2018-12-20

申请号：US16009822

申请日：2018-06-15

Applicant: NEC Laboratories America, Inc.

Inventor： Tan Yan ,  Haifeng Chen ,  LuAn Tang

IPC: G05B13/02 ,  G05B13/04 ,  B01D53/30

CPC classification number: G05B13/0265 ,  B01D53/30 ,  B01D2258/06 ,  G05B13/04

Abstract: A computer-implemented method, system, and computer program product are provided for anomaly detection. The method includes receiving, by a processor, sensor data from a plurality of sensors in a system. The method also includes generating, by the processor, a relationship model based on the sensor data. The method additionally includes updating, by the processor, the relationship model with new sensor data. The method further includes identifying, by the processor, an anomaly based on a fused single-variant time series fitness score in the relationship model. The method also includes controlling an operation of a processor-based machine to change a state of the processor-based machine, responsive to the anomaly.

公开(公告)号：US20180053111A1

公开(公告)日：2018-02-22

申请号：US15680831

申请日：2017-08-18

Applicant: NEC Laboratories America, Inc.

Inventor： Tan Yan ,  Dongjin Song ,  Haifeng Chen ,  Guofei Jiang ,  Tingyang Xu

IPC: G06N7/08 ,  G06F17/14 ,  G06F17/16

CPC classification number: H02J13/0006 ,  G05B17/02 ,  G06F17/142 ,  G06F17/16 ,  G06F17/18 ,  G06K9/00563 ,  G06K9/6244 ,  G06K9/6267 ,  G06N7/08 ,  G06N20/00

Abstract: Methods and systems for detecting anomalies include determining a predictive model for each pair of a set of time series, each time series being associated with a component of a system. New values of each pair of time series are compared to values predicted by the respective predictive model to determine if the respective predictive model is broken. A number of broken predictive models is determined. An anomaly alert is generated if the number of broken predictive models exceeds a threshold.

公开(公告)号：US20160282821A1

公开(公告)日：2016-09-29

申请号：US15079820

申请日：2016-03-24

Applicant: NEC Laboratories America, Inc.

Inventor： Haifeng Chen ,  Tan Yan ,  Guofei Jiang

IPC: G05B13/04 ,  G06F17/18

CPC classification number: G05B13/041 ,  G06F17/18

Abstract: Systems and methods for managing one or more physical systems, including determining system behavior switching based on time series data from one or more sensors in the system. Time series is divided into a plurality of segments, and each of the segments represents a system behavior. A fitness model is generated for each of the segments to determine whether to select each of the segments as invariants, and an ensemble of local relationship models are built for each of the time series for each invariant to identify local behavior switching points over time. The identified local behavior switching points of each invariant are aggregated by aligning the local switching points of all invariant segments, computing a density distribution of the aligned switching points, and extracting local maximas of the density distribution to determine the global switching points. System operations are controlled based on the determined system behavior switching.

Abstract translation: 用于管理一个或多个物理系统的系统和方法，包括基于系统中一个或多个传感器的时间序列数据确定系统行为切换。 时间序列分为多个段，每个段表示系统行为。 为每个段生成适应度模型，以确定是否选择每个段作为不变量，并为每个不变量的每个时间序列构建一个局部关系模型的集合，以识别随时间推移的局部行为切换点。 通过对齐所有不变段的局部切换点，计算对齐的切换点的密度分布，以及提取密度分布的局部最大值来确定全局切换点来聚合每个不变量的识别的局部行为切换点。 系统操作根据所确定的系统行为切换进行控制。