Title | Fast and high-resolution laser-ultrasonic imaging for visualizing subsurface defects in additive manufacturing components |
Author | |
Corresponding Author | Guo, Shifeng |
Publication Years | 2023-01
|
DOI | |
Source Title | |
ISSN | 0264-1275
|
EISSN | 1873-4197
|
Volume | 225 |
Abstract | Additive manufacturing (AM) is an emerging technique for efficient fabrication of individually tailored and complex geometry parts. The fabrication process is prone to induce various defects that can have detrimental effects on the AM components. Therefore, a reliable technique that enables monitoring the integrity of AM components and in return helping to optimize the fabrication parameters in mission-critical structures is highly demanded. This work presents a fast and high-resolution damage visualization method using laser-ultrasonic (LU) imaging technique for accurately detecting and quantifying the subsurface defects in printed AM components. Specifically, a fully noncontact LU scanning system is implemented to generate and detect high signal-to-noise ratio laser ultrasonic waves using a pulsed laser and laser Doppler vibrometer, respectively. A strategy for fast defect localization using Rayleigh waves with circular scans is firstly proposed. The high-resolution 3D synthetic aperture focusing technique (SAFT) imaging with raster scans is subsequently performed focusing around the located damage areas to stereoscopically visualize and quantify the subsurface defects. The reconstructed images are further processed and improved using Gaussian filter algorithm to obtain accurate defect shapes, sizes, and positions. The feasibility of the proposed method is eventually verified on AlSi10Mg and stainless steel (316L) components containing subsurface defects with various types and dimensions. The measured sizes are well consistent with the designed values, suggesting that it is a reliable inspection method for AM parts to ensure quality control and feedback. © 2022 The Authors |
Indexed By | |
Language | English
|
SUSTech Authorship | Others
|
Funding Project | This work was supported in part by the National Natural Science Foundation of China (Grant No. U2133213, 52071332), in part by the Department of Science and Technology of Guangdong Province (Grant No. 2019QN01H430, 2019TQ05Z654), in part by the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2022A1515010691, 2020A1515110218), in part by the Science and Technology Innovation Commission of Shenzhen (Grant No. ZDSYS20190902093209795, JCYJ20220818101215033, JCYJ20210324101200002).
|
WOS Accession No | WOS:000908051200004
|
Publisher | |
EI Accession Number | 20225013228292
|
EI Keywords | 3D printers
; Additives
; Damage detection
; Defects
; Focusing
; Image enhancement
; Pulsed lasers
; Signal to noise ratio
|
ESI Classification Code | Information Theory and Signal Processing:716.1
; Lasers, General:744.1
; Printing Equipment:745.1.1
; Chemical Agents and Basic Industrial Chemicals:803
; Materials Science:951
|
Data Source | EV Compendex
|
Citation statistics |
Cited Times [WOS]:0
|
Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/519709 |
Department | Department of Electrical and Electronic Engineering |
Affiliation | 1.Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen; 518055, China 2.Guangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen; 518055, China 3.University of Chinese Academy of Sciences, Beijing; 100049, China 4.Institute of Intelligent Manufacturing Technology, Shenzhen Polytechnic, Shenzhen; 518055, China 5.School of Mechanical Engineering and Mechanics, Ningbo University, Zhejiang, Ningbo; 315211, China 6.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen; 518055, China |
Recommended Citation GB/T 7714 |
Lv, Gaolong,Yao, Zhijun,Chen, Dan,et al. Fast and high-resolution laser-ultrasonic imaging for visualizing subsurface defects in additive manufacturing components[J]. Materials and Design,2023,225.
|
APA |
Lv, Gaolong.,Yao, Zhijun.,Chen, Dan.,Li, Yehai.,Cao, Huanqing.,...&Guo, Shifeng.(2023).Fast and high-resolution laser-ultrasonic imaging for visualizing subsurface defects in additive manufacturing components.Materials and Design,225.
|
MLA |
Lv, Gaolong,et al."Fast and high-resolution laser-ultrasonic imaging for visualizing subsurface defects in additive manufacturing components".Materials and Design 225(2023).
|
Files in This Item: | There are no files associated with this item. |
|
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment