A data augmentation approach for improving data-driven nonlinear ultrasonic characterization based on generative adversarial U-net-Reference-Cited by-同舟云学术

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A data augmentation approach for improving data-driven nonlinear ultrasonic characterization based on generative adversarial U-net

Published:2024-11 Issue: Volume:225 Page:110208
ISSN:0003-682X
Container-title:Applied Acoustics
language:en
Short-container-title:Applied Acoustics

Author:

Wu Peng,Liu Lishuai,Song Ailing,Xiang Yanxun^ORCID,Xuan Fu-Zhen

Publisher

Elsevier BV

Reference37 articles.

1. Creep damage characterization using nonlinear ultrasonic guided wave method: A mesoscale model;Xiang;J Appl Phys,2014

2. Comparison of changes in nonclassical (α) and classical (β) acoustic nonlinear parameters due to thermal aging of 9cr–1mo ferritic martensitic steel;Fahse;NDT E Int,2020

3. Experimental study of thermal degradation in ferritic cr–ni alloy steel plates using nonlinear lamb waves;Xiang;NDT E Int,2011

4. Investigation of the microstructure evolution in tp347hfg austenitic steel at 700°c and its characterization method;Zhang;J Acoust Soc Am,2020

5. Nonlinear ultrasonic technique for the characterization of microstructure in additive materials;Bellotti;J Acoust Soc Am,2021

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