US 11,783,099 B2
Autonomous surrogate model creation platform
James Albert Tallman, Glenville, NY (US); Eric Tucker, West Glenville, NY (US); Robert Zacharias, Saratoga Springs, NY (US); Andy Gallo, Duanesburg, NY (US); and Vince Russo, Loudonville, NY (US)
Assigned to GENERAL ELECTRIC COMPANY, Schenectady, NY (US)
Filed by General Electric Company, Schenectady, NY (US)
Filed on Aug. 1, 2018, as Appl. No. 16/51,753.
Prior Publication US 2020/0042659 A1, Feb. 6, 2020
Int. Cl. G06N 20/00 (2019.01); G06F 30/23 (2020.01); G06N 7/08 (2006.01); G06F 111/06 (2020.01); G06F 111/20 (2020.01); G06F 111/10 (2020.01)
CPC G06F 30/23 (2020.01) [G06N 7/08 (2013.01); G06N 20/00 (2019.01); G06F 2111/06 (2020.01); G06F 2111/10 (2020.01); G06F 2111/20 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A surrogate model creation computer system, comprising:
a user interface operative to interact with a subject matter expert via a subject matter device, wherein an output of the interaction is a scripted physics-based model workflow associated with an industrial asset, the scripted physics-based model workflow comprising a series of automatically performable steps adapted to create a trained surrogate digital model of the industrial asset, wherein the trained surrogate digital model is a simulation model of the industrial asset; and
a surrogate model creation engine, coupled to the user interface, adapted to:
automatically execute the scripted physics-based model workflow, in connection with a physics-based model of the industrial asset, to generate at least one response surface of the scripted physics-based model workflow, the response surface including a plurality of solution points;
train a surrogate digital model of the industrial asset using the response surface and a machine learning process to automatically create the trained surrogate digital model of the industrial asset;
arrange to output the trained surrogate digital model for use by a substantially real-time analytics package associated with the industrial asset;
constantly, via one or more runners, scan one or more databases of field product data for updated field data associated with the use of the trained surrogate digital model by the substantially real-time analytics package;
automatically receive from the one or more databases of field product data, updated field data;
automatically determine, by the runners, three or more downstream files that exist downstream of the updated databases, wherein a first of the three or more downstream files include the scripted physics-based model workflow, a second of the three or more downstream files include the response surface generated via execution of the scripted physics-based model workflow in connection with the physics-based model of the industrial asset and a third of the three or more downstream files include the trained surrogate model;
automatically update the downstream files with the updated field data;
determine, by the system, the updated field data is outside a range of input parameters used to generate the response surface;
automatically generate a collection of new operating points;
and
automatically re-train the trained surrogate digital model with automatically generated collection of new operating points.