Study on Internal Defect Detection Technology of Billet Based on Ultrasonic Tomography
LIU Huihe1,ZHENG Huifeng1,TANG Jiaxuan1,YAO Lei2
1. China Jiliang University, Hangzhou 310018, China
2. Key Laboratory of Acoustics and Vibration Precision Measuring Technology for State Market Regulation, Hangzhou, Zhejiang 310018, China
Abstract：To achieve accurate detection of internal defect morphology in billets, a priori knowledge-based ultrasonic tomographic imaging method is proposed. Firstly, the principle of fusing prior knowledge into ultrasonic tomographic imaging is elaborated, and the shortest path ray tracing method is used to improve the ultrasonic tomographic imaging. Then, the feasibility of the method is verified through finite element simulation analysis, and the acquisition scheme is discussed to determine the relevant detection parameters. Finally, an experimental detection system is built, and related validation experiments are conducted. Through processing and analyzing the imaging results of defect distribution, the results show that for the single pore defect specimen, the relative error of pore contour area is 2.84% with small position error. For the double-hole defective test block, the relative error is 5.45%, in which the hole far away from the transmitting probe has a larger position error. The method provides an idea and method for the application of ultrasonic tomography technology.
刘慧鹤,郑慧峰,唐佳玄,姚磊. 基于超声层析成像的钢坯内部缺陷检测技术研究[J]. 计量学报, 2024, 45(5): 714-721.
LIU Huihe,ZHENG Huifeng,TANG Jiaxuan,YAO Lei. Study on Internal Defect Detection Technology of Billet Based on Ultrasonic Tomography. Acta Metrologica Sinica, 2024, 45(5): 714-721.
DING H, LI X, WANG Z, et al. Ultrasonic nondestructive testing and characterization of internal defects of casting billet［J］. Steelmaking, 2019(3): 47-53.
GUO C B, HUANG Z J. Transmission speed of structural voice in polycrystalline metals［J］. Acta Acoustica Sinica, 1997, 34(1): 22-27.
FANG L D, KONG H Z, HAN B B, et al. Gas-liquid interface detection based on array ultrasonic sensor［J］. Journal of Metrology, 2022, 43(12): 1616-1621. )
［5］
王浩全. 超声阵列层析成像检测方法研究［D］. 太原: 中北大学, 2011.
LIU C, WANG L, CHANG M, et al. Ultrasound computed tomography［J］. Beijing Biomedical Engineering, 2002, 22(2): 152-155.
VRANA J, SCHRNER K, MOOSHOFER H, et al. Ultrasonic Computed Tomography-Pushing the Boundaries of the Ultrasonic Inspection of Forgings［J］. steel research international, 2018, 89(4): 1700448.
LIU L J, XIE Z H, YANG C. Ray tracing algorithm based on boundary linear time interpolation［J］. Journal of South China University of Technology (Natural Science Edition), 2014, 42(5): 23-28.
GUPTA M, KHAN M A, BUTOLA R, et al. Advances in applications of Non-Destructive Testing (NDT): A review［J］. Advances in Materials and Processing Technologies, 2022, 8(2): 2286-2307.
［10］
NOROSE Y, MIZUTANI K, WAKATSUKI N. Application of ultrasonic computerized tomography using time-of-flight measured by transmission method to nondestructive inspection for high-attenuation billets［J］. Japanese Journal of Applied Physics, 2014, 53(7S): 7-19
LAN C Q. Successful development of underwater ultrasonic detection imaging system［J］. Journal of Applied Acoustics, 1999, 18(4): 40.
［16］
PRYOR R W. Multiphysics modeling using COMSOL: a first principles approach［M］. Sudbury: Jones & Bartlett Publishers, 2009.
MA J. Application of ultrasonic nondestructive testing technology in welding defect detection of metal materials［J］. China Metals Bulletin, 2019(3): 195-196.
DOI T, MIYAMOTO R, WAKATSUKI N, et al. Transmission detection of internal defects in billets using shear ultrasonic waves［J］. Japanese Journal of Applied Physics, 2022, 61(SG): SG1039.
YAO B, WEN X L, JIAO L B, et al. Improved YOLOv3 algorithm for surface defect detection of aluminum profiles［J］. Acta Metrology Sinica, 2022, 43(10): 1256-1261. )
2024, Vol. 45 
