Advances in Postprocessing Technology for Laser Ultrasound Detection Signals: A Review

被引:4
作者
Lian, Yudong [1 ,2 ,3 ]
Xie, Luyang [1 ,2 ,3 ]
Han, Shiwei [1 ,2 ,3 ]
Du, Fenjiao [1 ,2 ,3 ]
Wang, Yulei [1 ,2 ,3 ]
Lu, Zhiwei [1 ,2 ,3 ]
机构
[1] Hebei Univ Technol, Ctr Adv Laser Technol, Tianjin 300401, Peoples R China
[2] Hebei Key Lab Adv Laser Technol & Equipment, Tianjin 300401, Peoples R China
[3] Tianjin Key Lab Elect Mat & Devices, Tianjin 300401, Peoples R China
基金
中国国家自然科学基金;
关键词
Defect reconstruction; intelligent processing; laser ultrasound; signal preprocessing; ultrasound imaging; TIME-REVERSAL; CLASSIFICATION; INSPECTION; WAVES; TREE;
D O I
10.1109/JSEN.2023.3325490
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the field of modern nondestructive testing (NDT), laser ultrasonic detection (LUD) technology has become a remarkable novel technology with its advantages of high-cost performance, noncontact detection, high accuracy, environmental adaptability, etc. Postprocessing of NDT ultrasonic waves to obtain more intuitive information reflecting the acoustic and mechanical properties of objects has also become an important step in modern quantitative NDT and one of the mainstream development directions. This article takes laser ultrasound detection as the entry point, introduces the typical techniques and principles of three major aspects including signal preprocessing, visualization processing, and intelligent defect reconstruction around the postprocessing of laser ultrasound detection signals after reception, compares and analyzes the results of different imaging algorithms, presents the intelligent processing methods commonly used in the field of ultrasound detection defect reconstruction, and briefly summarizes and outlooks on intelligent ultrasound signal processing technology.
引用
收藏
页码:28564 / 28578
页数:15
相关论文
共 104 条
[11]  
[陈尧 Chen Yao], 2021, [仪器仪表学报, Chinese Journal of Scientific Instrument], V42, P264
[12]   Defect inspection technologies for additive manufacturing [J].
Chen, Yao ;
Peng, Xing ;
Kong, Lingbao ;
Dong, Guangxi ;
Remani, Afaf ;
Leach, Richard .
INTERNATIONAL JOURNAL OF EXTREME MANUFACTURING, 2021, 3 (02)
[13]  
[陈尧 Chen Yao], 2019, [机械工程学报, Journal of Mechanical Engineering], V55, P25
[14]   Artificial Intelligence-Based Bolt Loosening Diagnosis Using Deep Learning Algorithms for Laser Ultrasonic Wave Propagation Data [J].
Dai Quoc Tran ;
Kim, Ju-Won ;
Tola, Kassahun Demissie ;
Kim, Wonkyu ;
Park, Seunghee .
SENSORS, 2020, 20 (18) :1-25
[15]   Compressed sensing [J].
Donoho, DL .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2006, 52 (04) :1289-1306
[16]  
[朵慕社 Duo Mushe], 2022, [制造业自动化, Manufacturing Automation], V44, P20
[17]   Full Wavefield Analysis and Damage Imaging Through Compressive Sensing in Lamb Wave Inspections [J].
Esfandabadi, Yasamin Keshmiri ;
De Marchi, Luca ;
Testoni, Nicola ;
Marzani, Alessandro ;
Masetti, Guido .
IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 2018, 65 (02) :269-280
[18]   Ultrasonic time-reversal-based super resolution imaging for defect localization and characterization [J].
Fan, Chengguang ;
Yu, Sunquan ;
Gao, Bin ;
Zhao, Yong ;
Yang, Lei .
NDT & E INTERNATIONAL, 2022, 131
[19]   The estimated cost of a search tree on binary words [J].
Fedotov, A ;
Ryabko, B .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2001, 47 (01) :326-329
[20]   Sizing of flaws using ultrasonic bulk wave testing: A review [J].
Felice, Maria V. ;
Fan, Zheng .
ULTRASONICS, 2018, 88 :26-42