Mel spectrogram–driven deep learning framework for acoustic emission-based manufacturing monitoring in wire arc additive manufacturing
Papers|更新时间:2026-06-05
|
Mel spectrogram–driven deep learning framework for acoustic emission-based manufacturing monitoring in wire arc additive manufacturing
梅尔频谱图驱动的深度学习框架:用于丝材电弧增材制造中基于声发射的制造监测
Journal of Reliability Science and EngineeringVol. 2, Issue 2, Pages: 1-14(2026)
作者机构:
School of Reliability and Systems Engineering, Beihang University, Xueyuan Road No.37, Haidian District, Beijing, People's Republic of China
Ningbo Institution of Technology (NIT), Beihang University, Ningbo 315832, People's Republic of China
作者简介:
Fei Gao received BS and PhD degrees in mechanical engineering from Xi'an Jiaotong University, Xi'an, China, in 2013 and 2018, respectively. He is currently an Associate Professor with the School of Reliability and Systems Engineering, Beihang University, Beijing, China. His research interests include structural health monitoring (SHM), nondestructive testing (NDT), and guided wave propagation.
Yishu Chen received a BS degree in reliability and safety engineering from Beihang University, Beijing, China, in 2022. He is currently pursuing a PhD degree in control science and engineering at Beihang University, Beijing, China. His research interests include structural health monitoring (SHM), nondestructive testing (NDT), and digital twin for fault diagnosis.
Jing Lin (Senior Member, IEEE) received BS, MS and PhD degrees in mechanical engineering from Xi'an Jiaotong University, Xi'an, China, in 1993, 1996 and 1999, respectively. From 2009 to 2018, he was a Professor with the School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China. He is currently the Dean of the School of Reliability and Systems Engineering, Beihang University, Beijing, China.
Yinmin Zhu received a BS degree in safety engineering from Beihang University, Beijing, China, in 2024. He is currently pursuing a PhD degree in electronic information engineering with Beihang University, Beijing, China. His research interests include structural health monitoring (SHM), nondestructive testing (NDT), and intelligent signal processing technology.
Yonghao Miao received BS degree in mechanical engineering and automation from the Wuhan University of Technology, Wuhan, China, in 2013, and a PhD degree in mechanical engineering from Xi'an Jiaotong University, Xi'an, China, in 2018. He is currently an Associate Professor with the School of Reliability and Systems Engineering, Beihang University, Beijing, China.
Jinghui Tian received a BS degree in measurement and control technology and instrumentation from Henan Polytechnic University, Jiaozuo, China, in 2018, and a PhD degree in mechanical design and theory from Yanshan University, Qinhuangdao, China, in 2024. He was a Visiting PhD Student with the Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy, from 2022 to 2023. He is currently a Postdoctoral Research Fellow with the Ningbo Institute of Technology, Beihang University, Ningbo, China. His research interests include transfer learning, information fusion, machinery condition monitoring, and intelligent fault diagnosis.