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Material grain size characterization method based on energy attenuation coefficient spectrum and support vector
Min Li1, Tong Zhou2, Yanan Song2
1Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China.
Abstract:
A grain size characterization method based on energy attenuation coefficient spectrum and support vector regression (SVR) is proposed. First, the spectra of the first and second back-wall echoes are cut into several frequency bands to calculate the energy attenuation coefficient spectrum. Second, the frequency band that is sensitive to grain size variation is determined. Finally, a statistical model between the energy attenuation coefficient in the sensitive frequency band and average grain size is established through SVR. Experimental verification is conducted on austenitic stainless steel. The average relative error of the predicted grain size is 5.65%, which is better than that of conventional methods.
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