DEEP LEARNING-BASED METHOD AND SYSTEM FOR PREDICTING FIRING PROPERTIES OF ANISOTROPIC MATERIAL BY USING INDENTATION RESPONSE DATA

WIPO Patent Application WO/2024/025111

A1

The present invention provides a deep learning-based method and system for predicting the firing properties of an anisotropic material by using indentation response data, the method and the system enabling the firing properties of an anisotropic material to be easily and quickly acquired non-destructively. The deep learning-based method for predicting the firing properties of an anisotropic material by using indentation response data, according to one embodiment of the present invention, comprises the steps of: preparing a plurality of data sets, about an anisotropic material for training, that are composed of indentation response data for training and firing property data for training; performing deep learning on a computer system by using the indentation response data for training as input values and the firing property data for training as output values; providing actual indentation response data about an anisotropic material to undergo prediction; and inputting the actual indentation response data into the computer system on which deep learning is performed, thereby predicting the firing properties of the anisotropic material to undergo prediction.

HAN HEUNG NAM (KR)
JEONG KYEONG JAE (KR)

PCT/KR2023/007074

February 01, 2024

May 24, 2023

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SEOUL NAT UNIV R&DB FOUNDATION (KR)

G01N11/00; G01N3/08; G01N3/42; G06N3/08

KR100702422B1	2007-04-03
KR102218594B1	2021-02-22
KR20220019552A	2022-02-17
KR20220030221A	2022-03-10
JP2016015092A	2016-01-28

LEE, In Haeng et al. (KR)

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