METHOD FOR BUILDING REDUCED ORDER MODEL BY USING PRINCIPAL COMPONENT VECTOR BASED ON SIMULATION AND PRINCIPAL COMPONENT CONSTANT THROUGH MACHINE LEARNING BASED ON MEASUREMENT DATA

Title:

METHOD FOR BUILDING REDUCED ORDER MODEL BY USING PRINCIPAL COMPONENT VECTOR BASED ON SIMULATION AND PRINCIPAL COMPONENT CONSTANT THROUGH MACHINE LEARNING BASED ON MEASUREMENT DATA

Document Type and Number:

WIPO Patent Application WO/2024/025385

Kind Code:

A1

Abstract:

The present invention relates to a method for building a reduced order model through machine learning by using measurement data, the method comprising: a CAE analysis step of obtaining a CAE analysis result by selecting, as parameters, operating variables or conditions that determine operating conditions of a target product or facility, and performing CAE analysis on cases sampled in a given parameter space; a principal component analysis step of extracting a principal component for the CAE analysis result obtained in the CAE analysis step and obtaining a principal component constant value; a machine learning model building step of building a machine learning model for the correlation between field measurement data and the principal component constant value by using the principal component constant value obtained in the principal component analysis step and the CAE analysis result corresponding to the field measurement data; and a simulation result acquisition step of acquiring a simulation result matching the field measurement data by using the principal component constant value obtained by inputting the field measurement data into the machine learning model.

Inventors:

HUH KANG YUL (KR)
HAN WOO JOO (KR)

Application Number:

PCT/KR2023/011039

Publication Date:

February 01, 2024

Filing Date:

July 28, 2023

Export Citation:

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Assignee:

PACE INC (KR)

International Classes:

G05B23/02; G05B13/04; G06F30/27; G06N20/00

Foreign References:

KR102266279B1	2021-06-17
KR20100116502A	2010-11-01
KR20210007735A	2021-01-20
KR102048243B1	2019-11-25
KR102261942B1	2021-06-07
KR102484587B1	2023-01-04

Other References:

PARK JINWOO, LEE WOOJIN, HUH KANG Y.: "Model order reduction by radial basis function network for sparse reconstruction of an industrial natural gas boiler", CASE STUDIES IN THERMAL ENGINEERING, ELSEVIER, vol. 37, 1 September 2022 (2022-09-01), pages 102288, XP093132590, ISSN: 2214-157X, DOI: 10.1016/j.csite.2022.102288

Attorney, Agent or Firm:

KANGIN PATENT LAW FIRM (KR)

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