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Patent Agency Ranking
公开(公告)号：US20230296078A1
公开(公告)日：2023-09-21
申请号：US17698040
申请日：2022-03-18
Applicant: General Electric Company
Inventor： Kalpesh Singal , Mustafa Tekin Dokucu , Fernando Javier D′Amato , Georgios Boutselis
CPC classification number: F03D7/046 , F03D7/0264 , F03D7/045 , F05B2270/1031 , F05B2270/1074 , F05B2270/328 , F05B2270/335 , F05B2270/709
Abstract: A method for providing backup control for a supervisory controller of at least one wind turbine includes observing, via a learning-based backup controller of the at least one wind turbine, at least one operating parameter of the supervisory controller under normal operation. The method also includes learning, via the learning-based backup controller, one or more control actions of the at least one wind turbine based on the operating parameter(s). Further, the method includes receiving, via the learning-based backup controller, an indication that the supervisory controller is unavailable to continue the normal operation. Upon receipt of the indication, the method includes controlling, via the learning-based backup controller, the wind turbine(s) using the learned one or more control actions until the supervisory controller becomes available again. Moreover, the control action(s) defines a delta that one or more setpoints of the wind turbine(s) should be adjusted by to achieve a desired outcome.
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2.发明授权公开(公告)号：US11790081B2
公开(公告)日：2023-10-17
申请号：US17229934
申请日：2021-04-14
Applicant: General Electric Company
Inventor： Fernando Javier D'Amato , Mustafa Tekin Dokucu , Hema Kumari Achanta, III , Kalpesh Singal , Masoud Abbaszadeh , Yuh-Shyang Wang , Karla Kvaternik , Souransu Nandi , Georgios Boutselis
CPC classification number: G06F21/554 , G05B15/02 , G06F9/45508 , G06N20/00 , G06F2221/034
Abstract: Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, a cyber-attack model predicts a plurality of operational impacts on the industrial asset resulting from a plurality of potential cyber-attacks. The cyber-attack model also predicts a corresponding plurality of potential mitigation responses. In operation, a cyber-attack impacting at least one component of the industrial asset is detected via the cyber-attack neutralization module and a protected operational impact of the cyber-attack is identified based on the cyber-attack model. The cyber-attack neutralization module selects at least one mitigation response of the plurality of mitigation responses based on the predicted operational impact and an operating state of the industrial asset is altered based on the selected mitigation response.
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公开(公告)号：US12180939B2
公开(公告)日：2024-12-31
申请号：US17698040
申请日：2022-03-18
Applicant: General Electric Company
Inventor： Kalpesh Singal , Mustafa Tekin Dokucu , Fernando Javier D'Amato , Georgios Boutselis
Abstract: A method for providing backup control for a supervisory controller of at least one wind turbine includes observing, via a learning-based backup controller of the at least one wind turbine, at least one operating parameter of the supervisory controller under normal operation. The method also includes learning, via the learning-based backup controller, one or more control actions of the at least one wind turbine based on the operating parameter(s). Further, the method includes receiving, via the learning-based backup controller, an indication that the supervisory controller is unavailable to continue the normal operation. Upon receipt of the indication, the method includes controlling, via the learning-based backup controller, the wind turbine(s) using the learned one or more control actions until the supervisory controller becomes available again. Moreover, the control action(s) defines a delta that one or more setpoints of the wind turbine(s) should be adjusted by to achieve a desired outcome.
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公开(公告)号：US12067124B2
公开(公告)日：2024-08-20
申请号：US17479370
申请日：2021-09-20
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Georgios Boutselis , Masoud Abbaszadeh
IPC: G06F21/57 , G06F16/2457
CPC classification number: G06F21/577 , G06F16/24578 , G06F2221/034
Abstract: The present application describes techniques for node selection and ranking for, e.g., attack detection and localization in cyber-physical systems, without relying on digital twins, computer models of assets, or operational domain expertise. The described techniques include obtaining an input dataset of values for a plurality of nodes (e.g., sensors, actuators, controllers, software nodes) of industrial assets, computing a plurality of principal components (PCs) for the input dataset according to variance of values for each node, computing a set of common weighted PCs based on the plurality of PCs according to variance of each PC, and ranking each node based on the node's contribution to the set of common weighted PCs.
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5.发明申请公开(公告)号：US20220334540A1
公开(公告)日：2022-10-20
申请号：US17229934
申请日：2021-04-14
Applicant: General Electric Company
Inventor： Fernando Javier D'Amato , Mustafa Tekin Dokucu , Hema Kumari Achanta, III , Kalpesh Singal , Masoud Abbaszadeh , Yuh-Shyang Wang , Karla Kvaternik , Souransu Nandi , Georgios Boutselis
Abstract: Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, a cyber-attack model predicts a plurality of operational impacts on the industrial asset resulting from a plurality of potential cyber-attacks. The cyber-attack model also predicts a corresponding plurality of potential mitigation responses. In operation, a cyber-attack impacting at least one component of the industrial asset is detected via the cyber-attack neutralization module and a protected operational impact of the cyber-attack is identified based on the cyber-attack model. The cyber-attack neutralization module selects at least one mitigation response of the plurality of mitigation responses based on the predicted operational impact and an operating state of the industrial asset is altered based on the selected mitigation response.
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