Affiliation:
1. CGN Inspection Technology Co., Ltd.
Abstract
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.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Zhejiang Province
Projects in Science and Technique Plans of Ningbo City
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering
Cited by
1 articles.
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