Grain size characterization of Ti-6Al-4V titanium alloy based on laser ultrasonic random forest regression

被引：7

作者：

Zhang, Juhao ^{[1
,2
]}

Wu, Jinfeng ^{[3
]}

Yin, Anmin ^{[1
,2
]}

Xu, Zhi ^{[1
,2
]}

Zhang, Zewen ^{[1
,2
]}

Yu, Huihui ^{[1
,2
]}

Lu, Yujie ^{[1
,2
]}

Liao, Wenchao ^{[1
,2
]}

Zheng, Lei ^{[1
,2
]}

机构：

[1] Ningbo Univ, Sch Mech Engn & Mech, Ningbo 315211, Zhejiang, Peoples R China

[2] Ningbo Univ, Sch Mech Engn & Mech, Zhejiang Key Lab Parts Rolling Technol, Ningbo 315211, Peoples R China

[3] CGN Inspect Technol Co Ltd, Suzhou 210521, Jiangsu, Peoples R China

来源：

APPLIED OPTICS | 2023年 / 62卷 / 03期

基金：

中国国家自然科学基金;

关键词：

RECRYSTALLIZATION; DECOMPOSITION; COMPOSITES;

D O I：

10.1364/AO.479323

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

In this paper, a random forest regression (RFR) rain size characterization method based on a laser ultrasound technique is investigated to predict the grain size of titanium alloy (Ti-6Al-4V). The longitudinal wave velocity of the ultrasound signal and the attenuation coefficient at different frequencies are used as the input and the grain size is used as the output. An RFR algorithm was used to develop a grain size prediction model. Meanwhile, the grain size calculation model based on conventional scattering attenuation was established by calibrating the n value in the classical scattering theory using the attenuation coefficients at different frequencies of ultrasonic signals. The results show that the RFR algorithm is feasible for the grain size characterization of titanium alloys. (c) 2023 Optica

引用

页码：735 / 744

页数：10

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