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    Computer system and method for monitoring the technical state of industrial process systems
    1.
    发明授权
    Computer system and method for monitoring the technical state of industrial process systems 有权

    公开(公告)号：US10969774B2

    公开(公告)日：2021-04-06

    申请号：US16576832

    申请日：2019-09-20

    Applicant: ABB Schweiz AG

    Inventor： Martin Hollender ,  Benjamin Kloepper ,  Michael Lundh ,  Moncef Chioua

    IPC: G06G7/00 ,  G05B23/02 ,  G05B13/04 ,  G06N20/10

    Abstract: An anomaly detection module is configured to apply a plurality of machine learning models to received technical status data to detect one or more indicators of an abnormal technical status prevailing in the industrial process system. The plurality of machine learning models are trained on historic raw or pre-processed sensor data and the anomaly detection module configured to generate the anomaly alert based on the one or more indicators. The received technical status data is assigned to signal groups and the generated anomaly alert is a vector with each vector element representing a group anomaly indicator for the respective signal group. Each vector element is determined by applying a respective group specific machine learning model.

    COMPUTER SYSTEM AND METHOD FOR MONITORING THE TECHNICAL STATE OF INDUSTRIAL PROCESS SYSTEMS
    2.
    发明申请
    COMPUTER SYSTEM AND METHOD FOR MONITORING THE TECHNICAL STATE OF INDUSTRIAL PROCESS SYSTEMS 审中-公开

    公开(公告)号：US20200012270A1

    公开(公告)日：2020-01-09

    申请号：US16576832

    申请日：2019-09-20

    Applicant: ABB Schweiz AG

    Inventor： Martin Hollender ,  Benjamin Kloepper ,  Michael Lundh ,  Moncef Chioua

    IPC: G05B23/02 ,  G05B13/04

    Abstract: An anomaly detection module is configured to apply a plurality of machine learning models to received technical status data to detect one or more indicators of an abnormal technical status prevailing in the industrial process system. The plurality of machine learning models are trained on historic raw or pre-processed sensor data and the anomaly detection module configured to generate the anomaly alert based on the one or more indicators. The received technical status data is assigned to signal groups and the generated anomaly alert is a vector with each vector element representing a group anomaly indicator for the respective signal group. Each vector element is determined by applying a respective group specific machine learning model.

    Motion Control System and Controllers for A Marine Vessel
    4.
    发明公开
    Motion Control System and Controllers for A Marine Vessel 审中-公开

    公开(公告)号：US20240004387A1

    公开(公告)日：2024-01-04

    申请号：US18342857

    申请日：2023-06-28

    Applicant: ABB Schweiz AG

    Inventor： Michael Lundh ,  Jonas Linder ,  Hamid Feyzmahdavian

    IPC: G05D1/02 ,  B63H21/21 ,  B63B79/40

    CPC classification number: G05D1/0206 ,  B63H21/21 ,  B63B79/40 ,  B63H2021/216

    Abstract: A high-level motion controller provides a lower-level thrust allocation with generalized forces demanded on the ship for the current instant of time as well as a prediction of future generalized forces {{circumflex over (τ)}D}t=0T demanded over a predicted future time, and optionally one or more other reference predictions, such as a time-varying velocity and position of the ship {{circumflex over (η)}D, {circumflex over (ν)}D}t=0T. When predictions of the future desired forces and torque are made available to the lower-level thrust allocation, the lower-level thrust allocation will be aware of what is needed in the future and use the predictions to make efficient changes towards the desired future references, when it generates control signals to thrusters available in the thruster system to distribute the desired generalized forces into individual forces of the individual thrusters.

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