1. 声-光信息融合

• Zhang Zhifen, Chen Shanben*, Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding, Mechanical Systems and Signal Processing，60 (2015) 151-165.     学术思想启蒙

• Wang J ，Zhang Zhifen*，Wen, Guangrui. On-line defect recognition of MIG lap welding  based on weld image and CMT voltage: Feature fusion and attention weights visualization. Journal of Manufacturing Processes.2023. 108. :430-444  学术思想延续

• 张志芬*,温广瑞等.基于声光全息相关融合的激光冲击强化表面质量实时评估,  机械工程学报. 2025.12     学术思想拓展

• Li Z, Zhang Z, Wang J, Du Z, Zhang S, Huang K, et al. In-situ porosity monitoring in laser powder bed fusion through acoustic signal and interpretable multi-sensor fusion. Mech Syst Signal Process 2025;241:113482https://doi.org/10.1016/j.ymssp.2025.113482.   学术思想拓展  
  

• 张志芬，温广瑞.《声光多源数据融合驱动焊接与增材智能制造》[M]. 西安交通大学出版社，2025，ISBN: 978-7-5693-1076-4     中文专著

• Zhifen Zhang，Guangrui Wen，Multiple sensing-driven Feature extraction and defect detection [M].  Springer Singapore，2025 ，ISBN: 978-981-96-4807-8    英文专著

• Zhifen. Zhang, G. Wen, S. Chen, On-Line Monitoring and Defects Detection of Robotic Arc Welding: A Review and Future Challenges, Transactions on Intelligent Welding Manufacturing2019, pp. 3-28.    英文长篇综述

• 张志芬, 陈善本, 温广瑞, 焊接智能化监测技术研究现状与展望, 焊接学报,(2024) 10-20    中文综述

• 焊接学报(中国机械工程学会T1期刊)24年11期特邀专刊“智能化焊接制造”客座编辑

• 中科院一区SCI《Journal of Manufacturing Processes》24年132期,“Innovative process, monitoring and control in the wire arc additive manufacturing”特刊编辑

2. 光学智能监测

• 张志芬,  杨哲,  任文静,   温广瑞.    电弧光谱深度挖掘下的铝合金焊接过程状态检测.  焊接学报, 2019,40(1):19-25.    2020年度机械工程学会优秀论文

• 张志芬，任文静，温广瑞*，“航空航天用铝合金机器人焊接内部气孔缺陷在线检测”，航空制造技术，2019.62(23-24).14-24       封面专稿

• Zhifen. Zhang, G. Wen, S. Chen, Weld image deep learning-based on-line defects detection using convolutional neural networks for Al alloy in robotic arc welding, Journal of Manufacturing Processes 45 (2019) 208-216.  SCI 一区，ESI 高被引，他引260余次 截止2026.05
  

• 张志芬,秦锐,都正尧,等.激光冲击强化过程监测及其质量在线评估：现状与挑战[J].航空制造技术,2023,66(Z1):14-25.   封面专稿

• 张志芬,刘子岷,秦锐等.基于ReliefF特征权重融合的激光冲击强化保护层烧损实时检测[J].光谱学与光谱分析,2023,43(08):2437-2445. (EI论文) 2021中国最具国际影响力学术期刊

• 白子键,张志芬*等.基于电弧光谱的核电堵管TIG焊接质量在线监测[J].焊接学报, 2024, 45(5):8-19.   封面论文 

• 白子键, 张志芬, 王杰, 张帅, 苏宇, 温广瑞, 陈雪峰, 基于光谱物理特征感知网络的DED稀释率监测, 焊接学报 第45卷(第11期) (2024) 95-100.  学术思想拓展

• Li Z, Zhang Zhifen, Chen Y, Wang Y, Du Z, Zhang Q, et al. In-situ optical emission spectroscopy monitoring of laser powder bed fusion based on spectral data prior knowledge and feature-decision level fusion network. Mech Syst Signal Process 2026;254:114406. https://doi.org/10.1016/j.ymssp.2026.114406.   学术思想拓展

3. 声学智能监测

• LI Z W, ZHENG H, ZHANG Z F, et al. On the use of acoustic emission methods for in-situ monitoring in metal additive manufacturing: A review study[J]. Additive Manufacturing Frontiers, 2026, 5(2): 200347.  与米兰理工大学Bianca 教授、Grasso教授合作综述SCI论文

• Z. Zhang, R. Qin, G. Li, Z. Du, Z. Li, Y. Lin, W. He, Deep learning-based monitoring of surface residual stress and efficient sensing of AE for laser shock peening, Journal of Materials Processing Technology 303 (2022).  受Jian Cao美国工程院院士邀请，参加JMPT (SCI一区)线上研讨会

• 《基于声发射的核电管道焊缝微量泄漏精准识别研究》2025年西安交通大学优秀硕士学位论文，于俨龙，指导教师：张志芬， 二〇二五年七月

• Z. Zhang, G. Wen, S. Chen, Audible Sound-Based Intelligent Evaluation for Aluminum Alloy in Robotic Pulsed GTAW: Mechanism, Feature Selection, and Defect Detection, IEEE Transactions on Industrial Informatics 14(7) (2018) 2973-2983.(SCI 中科院1区)

• Zhang Zhifen*, Xiang X, et al. Rebalancing Mel-frequency Cepstrum and parallel fusion model for surface hardness monitoring of laser shock peening using acoustic emission[J]. Mechanical Systems and Signal Processing, 2025, 223: 111912. (SCI 中科院1区)

•  R. Qin, Z.F. Zhang, J. Huang, Z.Y. Du, X.Z. Chen, Y. Su, G.R. Wen, W.F. He, X.F. Chen, Deciphering laser shock peening quality monitoring: Wavelet-driven network with interpretability, ADVANCED ENGINEERING INFORMATICS 62 (2024). (SCI 中科院1区)

•  S. Zhang, Z. Zhang, X. Chen, R. Qin, J. Wang, Z. Bai, Z. Li, J. Huang, Y. Su, G. Wen, X. Chen, Intra-layer and inter-layer monitoring of laser powder bed fusion defects based on airborne acoustic and g<SUP>n</SUP>-Res model: pore and deformation, VIRTUAL AND PHYSICAL PROTOTYPING 19(1) (2024). (SCI 中科院1区)

• Z. Zhang, E. Kannatey-Asibu, S. Chen, Y. Huang, Y. Xu, Online defect detection of Al alloy in arc welding based on feature extraction of arc spectroscopy signal, International Journal of Advanced Manufacturing Technology 79(9-12) (2015) 2067-2077. 

• Z. Zhang, H. Chen, Y. Xu, J. Zhong, N. Lv, S. Chen, Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding, Mechanical Systems and Signal Processing 60 (2015) 151-165.(SCI 中科院1区)

• Z. Zhang, H. Yu, N. Lv, S. Chen, Real-time defect detection in pulsed GTAW of Al alloys through on-line spectroscopy, Journal of Materials Processing Technology 213(7) (2013) 1146-1156. (SCI 中科院1区)

• R. Qin, Z. Zhang, J. Huang, Z. Du, X. Xiang, J. Wang, G. Wen, W. He, A novel physically interpretable end-to-end network for stress monitoring in laser shock peening, Computers in Industry 155 (2024). (SCI 中科院1区)

• J. Huang, Z. Zhang, R. Qin, Y. Yu, G. Wen, W. Cheng, X. Chen, Interpretable real-time monitoring of pipeline weld crack leakage based on wavelet multi-kernel network, Journal of Manufacturing Systems 72 (2024) 93-103. (SCI 中科院1区)

•  Z. Zhang, R. Qin, G. Li, Z. Du, G. Wen, W. He, A Novel Approach for Surface Integrity Monitoring in High-Energy Nanosecond-Pulse Laser Shock Peening: Acoustic Emission and Hybrid-Attention CNN, IEEE Transactions on Industrial Informatics 19(3) (2023) 2802-2813.   NSK 优秀论文  (SCI 中科院1区)

• R. Qin, Z. Zhang, J. Huang, J. Wang, Z. Du, G. Wen, W. He, Surface stress monitoring of laser shock peening using AE time-scale texture image and multi-scale blueprint separable convolutional networks with attention mechanism, Expert Systems with Applications 224 (2023). (SCI 中科院1区)

部分同行评价：

部分专利：

1. 张志芬,王杰,秦锐,李耿，一种电弧焊接成型缺陷的在线监测方法及装置，2023103088441，实质审查，20230323

2. 张志芬,王杰,秦锐,李耿，一种薄板搭接电弧焊偏移量在线识别方法、装置和设备，张志芬,王杰,秦锐,李耿，202310425403X，实质审查，20230419

3. 张志芬，李治文，张琦，都正尧，张帅，王杰，白子健，基于声信号高频信息的激光粉末床熔融缺陷在线监测方法， 2023.4.21，已提交

4. 张志芬，李治文，张琦，都正尧，张帅，王杰，白子健，基于声信号重要频段的激光粉末床熔融缺陷在线监测方法， 2023.4.21，已提交

5. 张志芬，于俨龙，黄婧，成玮，陈雪峰，温广瑞，一种基于声发射技术的管道泄漏裂纹形貌在线识别方法,    2023.06，已提交

6. 张志芬，秦锐，温广瑞，田增，何卫锋，黄婧，基于内部弹性波非线性特征的激光冲击强化实时监测方法，已公开，2021.7.9，2021102408509  已授权

7. 张志芬，李耿，秦锐，刘子岷，田增，何卫锋，温广瑞，基于声发射双通道极差的激光冲击强化缺陷在线检测方法，已公开，2021.9.3，CN 113340997 A             

8. 张志芬，李耿，秦锐，刘子岷，田增，何卫锋，温广瑞，一种激光冲击强化缺陷实时检测的声发射信号频段选择方法，已公开，2021.9.3，CN 113340995 A         

9. 张志芬，李耿，秦锐，刘子岷，田增，何卫锋，温广瑞，基于声发射衰减能量的激光冲击强化缺陷在线检测方法，已公开，2021.9.3，CN 113340996 A               

10. 张志芬，刘子岷，秦锐，李耿，何卫锋，温广瑞，基于模态声发射谱比值的激光冲击强化质量在线监测方法，已公开，2021.9.3，CN 113340493 A                       

11. 张志芬，刘子岷，秦锐，李耿，何卫锋，温广瑞，基于时窗能量衰减系数的激光冲击强化质量在线监测方法，已公开，2021.9.14，CN 113390963 A                       

12. 张志芬，刘子岷，秦锐，李耿，何卫锋，温广瑞，基于谐波小波频带能量的激光冲击强化质量在线监测方法，已公开，2021.9.3，CN 113340494 A

13. 张志芬，任文静，栾日维，杨哲，温广瑞，一种铝合金熔焊过程状态检测方法及其装置， 2018.05，已受理

14. 张志芬, 任文静,杨哲,温广瑞，一种交流钨极氩弧焊电弧声音信号特征快速提取方法， 发明专利，已授权， 2020.03.31， CN 109128446 B

15. 张志芬, 任文静,杨哲,温广瑞，机器人电弧焊焊接过程控制及多传感信号同步采集系统及方法，已授权，2020.01.17，  CN  108326393  B