Scalable hierarchical abnormality localization in cyber-physical systems

    公开(公告)号:US11503045B2

    公开(公告)日:2022-11-15

    申请号:US16261931

    申请日:2019-01-30

    Abstract: A cyber-physical system may have monitoring nodes that generate a series of current monitoring node values over time that represent current operation of the system. A hierarchical abnormality localization computer platform accesses a multi-level hierarchy of elements, and elements in a first level of the hierarchy are associated with elements in at least one lower level of the hierarchy and at least some elements may be associated with monitoring nodes. The computer platform may then determine, based on feature vectors and a decision boundary, an abnormality status for a first element in the highest level of the hierarchy. If the abnormality status indicates an abnormality, the computer platform may determine an abnormality status for elements, associated with the first element, in at least one level of the hierarchy lower than the level of the first element. These determinations may be repeated until an abnormality is localized to a monitoring node.

    Local and global decision fusion for cyber-physical system abnormality detection

    公开(公告)号:US10990668B2

    公开(公告)日:2021-04-27

    申请号:US16132705

    申请日:2018-09-17

    Abstract: Monitoring nodes may generate a series of current monitoring node values over time representing current operation of a cyber-physical system. A decision fusion computer platform may receive, from a local status determination module, an indication of whether each node has an initial local status of “normal”/“abnormal” and a local certainty score (with higher values of the local certainty score representing greater likelihood of abnormality). The computer platform may also receive, from a global status determination module, an indication of whether the system has an initial global status of “normal”/“abnormal” and a global certainty score. The computer platform may output, for each node, a fused local status of “normal” or “abnormal,” at least one fused local status being based on the initial global status. The decision fusion computer platform may also output a fused global status of “normal” or “abnormal” based on at least one initial local status.

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