南方科技大学知识苑(SUSTech KC): Automatic Quantification of Subsurface Defects by Analyzing Laser Ultrasonic Signals Using Convolutional Neural Networks and Wavelet Transform

题名	Automatic Quantification of Subsurface Defects by Analyzing Laser Ultrasonic Signals Using Convolutional Neural Networks and Wavelet Transform
作者	Guo，Shifeng 1; Feng，Haowen 2; Fenga，Wei 3; Lv，Gaolong 2; Chen，Dan 2; Liu，Yanjun4 ; Wu，Xinyu 5
发表日期	2021-10
DOI	10.1109/TUFFC.2021.3087949
发表期刊	IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 影响因子和分区
ISSN	1525-8955
卷号	68 期号:10页码:3216-3225
关键词	Convolutional neural networks laser ultrasonic signal nondestructive evaluation (NDE) numerical model subsurface defects wavelet transform
相关链接	[IEEE记录]
收录类别	SCI ; EI
学校署名	其他
EI入藏号	20213010684127
EI主题词	Convolution ; Convolutional neural networks ; Defects ; Feature extraction ; Frequency domain analysis ; Image compression ; Learning algorithms ; Machine learning ; Signal detection ; Ultrasonic applications
EI分类号	Information Theory and Signal Processing:716.1 ; Ultrasonic Applications:753.3 ; Mathematical Transformations:921.3 ; Materials Science:951
来源库	IEEE
全文链接	https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9449860
引用统计	被引频次[WOS]：24
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/242233
专题	工学院_电子与电气工程系
作者单位	1.Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen B 518055, P.R. China, and University of Chinese Academy of Sciences, Beijing 100049, China. (e-mail: sf.guo@siat.ac.cn) 2.Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen B 518055, P.R. China, and University of Chinese Academy of Sciences, Beijing 100049, China. 3.University of Chinese Academy of Sciences, Beijing 100049, China, and CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems B Shenzhen Institutes of Advanced Technology, Shenzhen B 518055, P.R. China. 4.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, China. 5.CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems B Shenzhen Institutes of Advanced Technology, Shenzhen B 518055, P.R. China, and Guangdong Provincial Key Lab of Robotics and Intelligent SystemB Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, ShenzhenB 518055, P.R. China.
推荐引用方式 GB/T 7714	Guo，Shifeng,Feng，Haowen,Fenga，Wei,et al. Automatic Quantification of Subsurface Defects by Analyzing Laser Ultrasonic Signals Using Convolutional Neural Networks and Wavelet Transform[J]. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control,2021,68(10):3216-3225.
APA	Guo，Shifeng.,Feng，Haowen.,Fenga，Wei.,Lv，Gaolong.,Chen，Dan.,...&Wu，Xinyu.(2021).Automatic Quantification of Subsurface Defects by Analyzing Laser Ultrasonic Signals Using Convolutional Neural Networks and Wavelet Transform.IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control,68(10),3216-3225.
MLA	Guo，Shifeng,et al."Automatic Quantification of Subsurface Defects by Analyzing Laser Ultrasonic Signals Using Convolutional Neural Networks and Wavelet Transform".IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 68.10(2021):3216-3225.