摘要
To address the challenge of visualizing internal defects within castings, ultrasonic nondestructive testing technology has been introduced for the detection and characterization of internal defects in castings. Ultrasonic testing is widely utilized for detecting and characterizing internal defects in materials, thanks to its strong penetration ability, wide testing area, and fast scanning speed. However, traditional ultrasonic testing primarily relies on one-dimensional waveforms or two-dimensional images to analyze internal defects in billets, which hinders intuitive characterization of defect quantity, size, spatial distribution, and other relevant information. Consequently, a three-dimensional (3D) layered characterization method of billets internal quality based on scanning acoustic microscope (SAM) is proposed. The method starts with a layered focus scanning of the billet using SAM and pre-processing the obtained sequence of ultrasonic images. Next, the ray casting is employed to reconstruct 3D shape of defects in billets, allowing for characterization of their quality by obtaining characteristic information on defect spatial distributions, quantity, and sizes. To validate the effectiveness of the proposed method, specimens of 42CrMo billets are prepared using five different processes, and the method is employed to evaluate their internal quality. Finally, a comparison between the ultrasonic image and the metallographic image reveals a difference in dimensional accuracy of only 2.94%. The results indicate that the new method enables visualization of internal defect information in billets, serving as a valuable complement to the traditional method of characterizing their internal quality.
基金
supported by the joint funds of the National Natural Science Foundation of China (Grant No. U22A20186)
the Open Foundation of Key Laboratory of Metallurgical Equipment and Control Technology (Wuhan University of Science and Technology) Ministry of Education (Grant No. MECOF2019804)
the Foundation of Key Technologies R&D Program of Guangdong Province (Grant No. 2020B0101130007).