职称：讲师
部门：工学院
电子邮件：dr.pengchen@foxmail.com(优先)
pengchen@alu.uestc.edu.cn
External Profile:https://drpengchen.vip.cpolar.cn/(Primary)
https://dr.pengchen.org.cn/
办公地址：机电楼301(I)
个人简介：
陈鹏，工学博士，硕士研究生导师，汕头大学卓越人才计划 (优秀青年人才) ，汕头市高层次人才(B类)，国家自然科学基金通讯评审专家，美国电子电气工程师学会会员 (IEEE Member)，中国振动工程学会信号处理分会理事、动态测试专业委员会理事及转子动力学分会理事。 2020年博士毕业于电子科技大学，获工学博士学位 (导师：加拿大工程院院士 Ming J. Zuo教授)，2019-2020年比利时鲁汶大学 (KU Leuven) 联合培养博士研究生, 2018年University of Pretoria南非科学院院士 Prof. P. Stephan Heyns 团队访问研究学者。主持承担(过)国家自然科学基金项目、广东省基础与应用基础研究基金面上项目、广东省科技计划项目等5项，参与国家重点研发计划项目、国家自然科学基金重点项目以及国家自然科学基金面上项目等6项。以第一/通讯作者发表SCI检索的JCR分区/中科院分区一区Top期刊论文20余篇，授权发明专利6项，并担任 IEEE INTERNET THINGS、IEEE T IND INFORM、IEEE T IND ELECTRON、IEEE T INSTRUM MEAS 、IEEE T RELIAB、MECH SYST SIGNAL PR、KNOWL-BASED SYST、ADV ENG INFORM等国际期刊同行评议审稿人。
主要研究方向/领域：信号及声学信息处理 (多尺度时频表征，干扰信号抑制、稀疏信号处理)、人工智能 (深度学习，视觉计算，图像/语音超分辨)、智能交互(智能传感、无线感知、人机协同)、故障预测与健康管理以及其在智能交通、风电产业、工业伺服机器人、智能制造系统的关键组件中的应用。
工作经历
2021/03-至今 汕头大学
2016/05-2018/12 UoG-UESTC Joint School,
1) Glasgow Teaching assistant (GTA) in Dynamic Control (Spring 2016, 2017 and 2018) With Dr. Julien Le Kernec
2) GTA in Professional Practice (Spring 2018) with Associated Prof. Lei Li,
3) GTA in Control (Fall 2017 and 2018) with Associated Prof. Kelum Gamage,
4) GTA in Digital Communication (Fall 2016, 2017 and 2018) with Prof. Muhammad Imran and Dr. Sajjad Hussain
2012/09-2014/07，中裕摩托车有限公司，工程师
科研/教学项目
[1] 国家自然科学基金，风电齿轮箱耦合信号时频特征表征增强及融合金字塔模型研究，52105111, 01/2022-12/2024（项目负责人）
[2] 广东省基础与应用基础研究基金 (自然科学基金面上项目) ，海上浮式风机关键传动件运行状态监测与故障诊断方法研究，2022A1515010859，01/2022-12/2024（项目负责人）
[3] 广东省科技专项资金项目，海上风力机传动链运行状态监测与故障诊断方法研究，STKJ2021171，10/2021-09/2023（项目负责人）
[4] 汕头大学科研启动项目，风电关键部件耦合信号特征表征及融合网络模型研究，NTF21029，01/2022-04/2024（项目负责人）
[5] 基于《机械智能运维基础》的课程思政教学与实践，教学质量与教学改革工程项目, 10/2023-10/2025（项目负责人）
[6] 国家重点研发计划，物理知识与运行数据驱动的重大装备异常检测与故障诊断，2018YFB1702401，2019/01-2022/12 (参与)
[7] 国家自然科学基金重点项目，高速列车运行风险评估及调控基础理论与方法，61833002，2019/01-2023/12（参与）
[8] 国家自然科学基金重点项目，多重不确定因素下的智能电网风险调度理论与方法研究，51537010，01/2019-12/2023（参与）
[9] 国家重点研发计划，放射治疗装备可靠性与工程化技术研究，2017YFC0108400，08/2017 - 07/2019（参与）
[10] 国家自然科学基金面上项目，行星齿轮传动系统故障诊断与动态可靠性评估研究，51375078，2014/01-2017/12 （参与）
[11] 中央高校基本业务费项目，风力发电传动行星齿轮箱载荷波动过程故障诊断技术研究， ZYGX2016J111，08/2017-12/2018（参与）
部分代表性论文
(最新发表论文见https://drpengchen.vip.cpolar.cn/research-work/)
[1] Peng Chen*, Zhigang Ma, Chaojun Xu, Yaqiang Jin, Chengning Zhou, Self-supervised transfer learning for remote wear evaluation in machine tool elements with imaging transmission attenuation, IEEE Internet of Things Journal, 2024, DOI: 10.1109/JIOT.2024.3382878.
[2] Peng Chen*, Yuhao Wu, Chaojun Xu, Yaqiang Jin, Chengning Zhou, Markov modeling of signal condition transitions for bearing diagnostics under external interference conditions, IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-8, 2024, 3518308, DOI: 10.1109/TIM.2024.3383497.
[3] Peng Chen*, Chaojun Xu, Zhigang Ma, Yaqiang Jin, A Mixed Samples-Driven Methodology Based on Denoising Diffusion Probabilistic Model for Identifying Damage in Carbon Fiber Composite Structures, IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-11, 2023, 3513411, DOI: 10.1109/TIM.2023.3267522.
[4] Peng Chen*, Yuhao Wu, Chaojun Xu, Adaptive signal regime for identifying transient shifts: A novel approach toward fault diagnosis in industrial equipment, IEEE Transactions on Industrial Informatics, 2023.
[5] Peng Chen*, Yuhao Wu, Dynamic transient noise-resilient fault diagnosis in industrial systems: Markov-based signal conditioning transformation modeling, IEEE Transactions on Industrial Electronics, 2023.
[6] Peng Chen*, Zhigang Ma, et. al., Scale-aware Domain Adaptation for Surface Defects Detection on Machine Tool Components in Contaminant Measurements, IEEE Transactions on Instrumentation and Measurement, 2023.
[7] Peng Chen*, Yuhao Wu, et. al., Interference suppression of non-stationary signals and bearing diagnosis under transient noise environments, IEEE Transactions on Reliability, 2023.
[8] Peng Chen*, Junxiao Ma, Chaojun Xu, Semi-supervised consistency models for automated defect detection in carbon fiber composites with limited data, IEEE Transactions on Automation Science and Engineering, 2023.
[9] Peng Chen*, Zhigang Ma, Zheng Li, Yaqiang Jin, Shui Fan, Cross-scale feature blending framework for surface defect identification in machine tool elements resilient to contaminant interference, IEEE Transactions on Automation Science and Engineering, 2023.
[10] Peng Chen*, Zhigang Ma, Zheng Li, Chaojun Xu, Shuai Fan, Masked auto-encoders remote assessment of machine tool components: A pixel loss adaptive retrieval methodology for reliable fault diagnosis, Mechanical System and Signal Processing, 2023.
[11] Chaojun Xu, Peng Chen*, Zheng Li, Zhigang Ma, Chengning Zhou, Cyclicalnet: Modeling temporal dependencies with 2d shifts for exploring underlying patterns in sequential vibration signals, Mechanical System and Signal Processing, 2023.
[12] Peng Chen, Yu Li, K. S. Wang, M. J. Zuo, P. S. Heyns, Stephan Baggeröhr, A threshold self-setting condition monitoring scheme for wind turbine generator bearings based on deep convolutional generative adversarial networks, Measurement (2021) Volume 167, 108234, DOI: 10.1016/j.measurement.2020.108234.
[13] Peng Chen, Yu Li, K. S. Wang, M. J. Zuo, A novel knowledge transfer network with fluctuating operating conditions adaptation for bearing fault pattern recognition, Measurement (2020) Volume 158, 107739, DOI: 10.1016/j.measurement.2020.107739.
[14] Peng Chen, Yu Li, K. S. Wang, M. J. Zuo, An automatic speed adaptation neural networks model for planetary gearbox fault diagnosis under time-varying operating conditions, Measurement (2021) Volume 171, 108784, DOI: 10.1016/j.measurement.2020.108784.
[15] Peng Chen, Yu Li, K. S. Wang, M. J. Zuo, Dongdong Wei, An ameliorated synchroextracting transform based on upgraded local instantaneous frequency approximation. Measurement (2019) Volume 148, 106953, DOI: 10.1016/j.measurement.2019.106953.
[16] Peng Chen, K. S. Wang, M. J. Zuo, Recursive mapping demodulation high order synchroextracting transform, Mechanical Systems and Signal Processing, 2021
[17] Peng Chen, K. S. Wang, M. J. Zuo, A generalized synchroextracting transform for fast and strong frequency modulated signal analysis, Condit. Monitor. Diagnost. Eng. Manage. (2018) 189-196.
[18] Peng Chen, K. S. Wang, Ke Feng, Application of order-tracking Holospectrum to cracked rotor fault diagnostics under nonstationary conditions, in: Prognostics and System Health Management Conference (PHM-Chengdu), 2016, IEEE, pp. 1-6.
授权发明专利
[1] 陈鹏，吴宇豪，许朝峻，高嘉，一种非高斯噪声环境下的轴承故障诊断方法、系统及设备，2024，中国，ZL 202410063788.4
[2] 陈鹏，许朝峻，马志刚，张春，去噪扩散样本增量学习的碳纤维材料损伤检测方法及装置，2022，中国，ZL 202211595005.4
[3] 陈鹏，王科盛，李宇，杨滨源，风机叶片光纤载荷应变特征提取及裂纹监测方法, 2019.12.31, 中国，CN 108592812 B
[4] 陈鹏，王科盛，一种基于二阶同步提取变换的强转速特征提取方法, 2018.08.10, 中国，CN 108388839 A
[5] 王科盛，李宇，陈鹏，何倩鸿，基于深度卷积对抗神经网络的旋转机械在线故障监测方法, 2018.10.12, 中国，CN 108647786 B
[6] 王科盛，冯珂，王况，韦冬东，陈鹏，宋理伟，基于轴心轨迹的旋转机械转速计算装置及方法, 2019.05.21, 中国，CN 106126840 B
