利用激光超声技术, 研究生产中常见的弧形表面缺陷的无损检测方法。首先基于热弹机制建立弧形表面缺陷检测的有限元仿真模型, 探究不同尺寸参数的缺陷对表面波反射回波及透射波的影响; 然后采用经验模态分解法对带有缺陷信息的反射回波和透射波信号进行了分解, 提取相应特征频率的信号进行叠加; 最后根据超声特征参数的变化规律, 建立了缺陷深度的预测模型。结果表明, 利用透射波特征参数计算得到的缺陷深度与实际缺陷深度相比的最大误差仅为0.6%, 因此提出的预测模型具有较高的精度, 可用于弧形表面缺陷的现场检测。

The purpose of this study is to investigate the specific method of laser ultrasonic nondestructive testing technology applied to the detection of arc surface defects commonly found in industrial production. To verify the influence of different dimensional parameters of defects on the reflected and transmitted surface waves, a finite element model for the detection of arc-shaped surface defects was established based on the ultrasound excitation mechanism by thermoelastic effect. Meanwhile, the empirical mode decomposition method was used to process the signal data to extract the reflected and transmitted waves of defects and superimpose the signal components of corresponding characteristic frequencies. Results reveal the changing laws of the relevant ultrasonic characteristic parameters. Based on this, two prediction models for the depth of arc surface defects are established. By comparison and analysis, the maximum error between the defect depth calculated by using the transmission wave parameter model, and the actual defect depth is only 0.6%. Therefore, the proposed defect depth prediction model provides a feasible solution for the on-site detection of arc surface defects with high accuracy.