Longitudinal Wave Defect Detection Technology Based on Ablation Mechanism

Author:

Wang Jian12,Guo Xing3,Xun Yanqin14ORCID,Liu Junzuo1,Guo Xin12ORCID,Li Ya12

Affiliation:

1. State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China

2. School of Information and Communication Engineering, North University of China, Taiyuan 030051, China

3. JINXI Group Shanxi Jiangyang Chemical Co., Taiyuan 030051, China

4. Electronic Information Science and Technology, Xinzhou Normal University, Xinzhou 034000, China

Abstract

For laser ultrasound in the thermoelastic mechanism, excitation of ultrasonic body wave signal is weak, it is not easy to realize the detection of deep defects inside the workpiece. While the ablation mechanism produces a high and practical ultrasonic signal-to-noise ratio, this paper is based on the generation mechanism of laser ablation excitation of ultrasonic waves, the establishment of laser ultrasound in the ablation mechanism in the aluminum plate excitation and propagation of ultrasonic numerical model, through the solution, obtained the ultrasonic acoustic field map, discussed the ablation mechanism of the laser ultrasonic body wave acoustic field directionality. Additionally, the preliminary verification of the validity of the model is presented. Then, in order to explore the application potential of high signal-to-noise ratio longitudinal waves in defect detection, defects of different depths are preset in the model for simulation calculations, and waveform and acoustic field analyses are performed on the simulation results to study the ultrasonic propagation paths inside the member and the interaction with the defects, and the transverse position and depth of the internal defects are judged by using B-scan imaging. Finally, experimental validation is carried out. The experimental results are highly consistent with the simulation model, and the defect experiments can qualitatively determine the location of internal defects and verify the practicality and accuracy of the model.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanxi Province

Publisher

MDPI AG

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