公开(公告)号：US20230408451A1

公开(公告)日：2023-12-21

申请号：US18331253

申请日：2023-06-08

Applicant: DOOSAN ENERBILITY CO., LTD

Inventor： June Sung SEO ,  Jun Woo Yoo ,  Jung Min Lee

IPC: G01N29/06 ,  G01N29/44

CPC classification number: G01N29/0645 ,  G01N29/4481 ,  G01N2291/023

Abstract: The embodiments of the present disclosure relate to an ultrasonic flaw-detection system and an ultrasonic flaw-detection method. The ultrasonic flaw-detection system may include: an ultrasonic flaw-detection device configured to transmit an ultrasonic wave to a detection target, collect an ultrasonic echo wave reflected from the detection target, and then generate a signal data; a signal data preprocessor configured to preprocesses the signal data; a defect candidate group selection unit configured to select a defect candidate group based on the preprocessed signal data and generate defect candidate signal data based on the selection; an image data generator configured to generate image data based on the defect candidate signal data included in the defect candidate group; and a defect determination unit configured to determine whether there is a defect in the defect candidate group based on the image data.

公开(公告)号：US12229932B2

公开(公告)日：2025-02-18

申请号：US17476555

申请日：2021-09-16

Applicant: DOOSAN ENERBILITY CO., LTD

Inventor： Jung Min Lee ,  Jung Moon Kim

IPC: G06T3/00 ,  G06T5/40 ,  G06T5/50 ,  G06T5/70 ,  G06T7/00 ,  G06T11/00

Abstract: A method of generating a defect image for deep learning and a system therefor are provided. The method and the system are intended to be used in generating training data for an artificial intelligence algorithm. More specifically, the training data are defect images required to train an algorithm that identifies a defect from a product.

公开(公告)号：US11544429B2

公开(公告)日：2023-01-03

申请号：US16698948

申请日：2019-11-27

Applicant: DOOSAN ENERBILITY CO., LTD.

Inventor： Jung Min Lee ,  Byoung Hwa Lee

IPC: G06F30/27 ,  G01N33/22 ,  G06N20/00 ,  G06F119/08

Abstract: An apparatus and method predict an initial deformation temperature of coal without an additional test by using a predictive model. The apparatus includes a parameter extractor configured to analyze characteristics of test coal and to extract parameters of the test coal based on the test coal characteristic analysis; a temperature analyzer configured to analyze an initial deformation temperature (IDT) of the test coal; a modeler configured to derive an IDT predictive model for predicting the test coal IDT using the extracted parameters of the test coal and the test coal IDT; and a predictor configured to predict an initial deformation temperature (IDT) of target coal to be supplied to the coal-fired power plant by substituting parameters of the target coal into the IDT predictive model. The test coal characteristics are analyzed by ash component analysis, elementary analysis, industrial analysis, or calorific value analysis.