State Key Laboratory of Fluid Power Components and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China.
State Key Laboratory of Fluid Power Components and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China.
Ultrasonics. 2023 Jul;132:106983. doi: 10.1016/j.ultras.2023.106983. Epub 2023 Mar 15.
Laser ultrasonic technology has been widely used in surface defect detection attribute to its non-contact, non-destructive and high spatial resolution characteristics. This paper proposes a surface defect quantitative detection method using laser-generated Rayleigh wave with broadband local wavenumber estimation. In this method, considering the broadband characteristics of laser-generated Rayleigh wave, the broadband local wavenumber estimation is presented to achieve the defect imaging accurately, and then the defect geometric parameters are estimated based on image segmentation. A surface defect detection experiment using the laser ultrasonic detection system is conducted to verify the effectiveness of the proposed method. The experimental results show that the proposed method has superior imaging effect for vertical and inclined defects than the standing wave energy method or reflected wave energy method. Besides, the geometric parameters such as length, width, and inclination angle of a surface defect can be accurately identified by the proposed method, the errors of vertical defects are 1.6% in length and 4.0% in width respectively, as well as the maximum and minimum error of inclined defects are 5.0% and 1.28% in inclination angle respectively. The research results provide a potential application for the fast and non-destructive surface defect detection of metal structures.
激光超声技术具有非接触、无损和高空间分辨率等特点，已广泛应用于表面缺陷检测。本文提出了一种基于激光产生的瑞利波宽带局部波数估计的表面缺陷定量检测方法。该方法考虑到激光产生的瑞利波的宽带特性，提出了宽带局部波数估计方法，以实现准确的缺陷成像，然后基于图像分割估计缺陷的几何参数。利用激光超声检测系统进行了表面缺陷检测实验，验证了所提方法的有效性。实验结果表明，与驻波能量法或反射波能量法相比，该方法对垂直和倾斜缺陷具有更好的成像效果。此外，该方法还可以准确识别表面缺陷的长度、宽度和倾斜角等几何参数，垂直缺陷的长度误差为 1.6%，宽度误差为 4.0%，倾斜缺陷的最大和最小倾斜角误差分别为 5.0%和 1.28%。研究结果为金属结构的快速无损表面缺陷检测提供了一种潜在的应用。
