INDUSTRIAL CONTROL SYSTEM WITH MACHINE LEARNING FOR COMPRESSORS

    公开(公告)号:US20210026334A1

    公开(公告)日:2021-01-28

    申请号:US16518523

    申请日:2019-07-22

    Abstract: A compressor controller for operating a compressor within an industrial automation environment is provided. The compressor controller includes a control module, configured to control the compressor via control settings, and a machine learning module, coupled with the control module. The machine learning module is configured to receive a set of supervised data related to the compressor, and to train with the supervised data to produce a Newtonian physics model representing the inputs and outputs of the compressor within the industrial automation environment. The machine learning module is also configured to receive performance data related to the compressor, receive environment data related to the compressor, and to process the performance data and environment data to produce predicted future performance data for the compressor, and to produce control settings for the compressor.

    SYNCHRONIZATION OF INDUSTRIAL AUTOMATION PROCESS SUBSYSTEMS

    公开(公告)号:US20210048798A1

    公开(公告)日:2021-02-18

    申请号:US16543112

    申请日:2019-08-16

    Abstract: Techniques to facilitate synchronization of industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives time-series industrial process data associated with a plurality of process subsystems of an industrial automation process. The time-series industrial process data is fed into a machine learning model associated with the industrial automation process to dynamically generate a process duration prediction for a first one of the process subsystems and responsively determine an updated set point for a second one of the process subsystems based on the process duration prediction for the first one of the process subsystems. The updated set point for the second one of the process subsystems is provided to an industrial controller associated with the second one of the process subsystems.

    SYNCHRONIZATION OF INDUSTRIAL AUTOMATION PROCESS SUBSYSTEMS

    公开(公告)号:US20220244711A1

    公开(公告)日:2022-08-04

    申请号:US17659742

    申请日:2022-04-19

    Abstract: Techniques to facilitate synchronization of industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives time-series industrial process data associated with a plurality of process subsystems of an industrial automation process. The time-series industrial process data is fed into a machine learning model associated with the industrial automation process to dynamically generate a process duration prediction for a first one of the process subsystems and responsively determine an updated set point for a second one of the process subsystems based on the process duration prediction for the first one of the process subsystems. The updated set point for the second one of the process subsystems is provided to an industrial controller associated with the second one of the process subsystems.

    Synchronization of industrial automation process subsystems

    公开(公告)号:US11340594B2

    公开(公告)日:2022-05-24

    申请号:US16543112

    申请日:2019-08-16

    Abstract: Techniques to facilitate synchronization of industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives time-series industrial process data associated with a plurality of process subsystems of an industrial automation process. The time-series industrial process data is fed into a machine learning model associated with the industrial automation process to dynamically generate a process duration prediction for a first one of the process subsystems and responsively determine an updated set point for a second one of the process subsystems based on the process duration prediction for the first one of the process subsystems. The updated set point for the second one of the process subsystems is provided to an industrial controller associated with the second one of the process subsystems.

    Industrial control system with machine learning for compressors

    公开(公告)号:US11340592B2

    公开(公告)日:2022-05-24

    申请号:US16518523

    申请日:2019-07-22

    Abstract: A compressor controller for operating a compressor within an industrial automation environment is provided. The compressor controller includes a control module, configured to control the compressor via control settings, and a machine learning module, coupled with the control module. The machine learning module is configured to receive a set of supervised data related to the compressor, and to train with the supervised data to produce a Newtonian physics model representing the inputs and outputs of the compressor within the industrial automation environment. The machine learning module is also configured to receive performance data related to the compressor, receive environment data related to the compressor, and to process the performance data and environment data to produce predicted future performance data for the compressor, and to produce control settings for the compressor.

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