Quantitative detection of surface defect using laser-generated Rayleigh wave with broadband local wavenumber estimation

Jun He; Xuekun Liu; Qichao Cheng; Shixi Yang; Miaoshuo Li

doi:10.1016/j.ultras.2023.106983

Quantitative detection of surface defect using laser-generated Rayleigh wave with broadband local wavenumber estimation

Ultrasonics. 2023 Jul:132:106983. doi: 10.1016/j.ultras.2023.106983. Epub 2023 Mar 15.

Authors

Jun He¹, Xuekun Liu¹, Qichao Cheng², Shixi Yang³, Miaoshuo Li¹

Affiliations

¹ 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.
² 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. Electronic address: qccheng@zju.edu.cn.
³ 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. Electronic address: yangsx@zju.edu.cn.

PMID: 36944300
DOI: 10.1016/j.ultras.2023.106983

Abstract

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.

Keywords: Broadband local wavenumber estimation; Image segmentation; Laser-generated Rayleigh wave; Quantitative detection.