18336491. ARTIFICIAL INTELLIGENCE BASED DATA-DRIVEN INTERCONNECTED DIGITAL TWINS (General Electric Company)
Contents
ARTIFICIAL INTELLIGENCE BASED DATA-DRIVEN INTERCONNECTED DIGITAL TWINS
Organization Name
Inventor(s)
Masoud Abbaszadeh of Clifton Park NY (US)
Johan Michael Reimann of Ballston Spa NY (US)
Hema K Achanta of Schenectady NY (US)
ARTIFICIAL INTELLIGENCE BASED DATA-DRIVEN INTERCONNECTED DIGITAL TWINS
This abstract first appeared for US patent application 18336491 titled 'ARTIFICIAL INTELLIGENCE BASED DATA-DRIVEN INTERCONNECTED DIGITAL TWINS
Original Abstract Submitted
In some embodiments, a system node data store may contain historical system node data associated with normal operation of an industrial asset, and a plurality of artificial intelligence model construction platforms may receive historical system node data. Each platform may then automatically construct a data-driven, dynamic artificial intelligence model associated with the industrial asset based on received system node data. The plurality of artificial intelligence models are interconnected and simultaneously trained to create a digital twin of the industrial asset. A synthetic disturbance platform may inject at least one synthetic disturbance into the plurality of artificial intelligence models to create, for each of a plurality of monitoring nodes, a series of synthetic disturbance monitoring node values over time that represent simulated abnormal operation of the industrial asset.
