陈昊，男，中共党员，讲师，工学博士，硕士研究生导师。2016年于华中科技大学获学士学位，2020年于华中科技大学获硕士学位，2024年6月博士毕业于澳门大学，同年8月入职yl6809永利集团，迄今发表论文12篇（第一作者8篇），主持国家自然科学基金青年项目1项、校基金1项。
主要研究方向：
旋转机械故障诊断,机器学习,人工智能
代表性科研项目：
迄今为止主持和参与多项纵向及横向课题，主要如下：
[1] 国家自然科学基金青年项目, 52505569, 可解释性特征解耦驱动的风机齿轮箱变工况故障鲁棒诊, 2026-01至2028-12 主持
代表性论文：
[1]H. Chen, X.-b. Wang and Z. -X. Yang, "Fast Robust Capsule Network With Dynamic Pruning and Multiscale Mutual Information Maximization for Compound-Fault Diagnosis," IEEE/ASME Transactions on Mechatronics, vol. 28, no. 2,pp. 838-847, April 2023, doi: 10.1109/TMECH.2022.3214865. (JCRQ1, 中科院一区 Top, 影响因子:5.867)
[2] Yang, Z.X., Li, C. S., Wang, X. B., & Chen, H.* (2022). “Intelligent fault monitoring and diagnosis of tunnel fans using a hierarchical cascade forest,” ISA transactions, 136(2023):442-454. (JCR Q1, 中科院二区 Top,影响因子: 7.3)
[3] Chen, H., Li, C., Yang, W., Liu, J., An, X., & Zhao, Y. "Deep balanced cascade forest: An novel fault diagnosis method for data imbalance." ISA transactions, 126(2022): 428-439. (JCR Q1, 中科院二区 Top,影响因子: 7.3)
[4] H. Chen, X. -B. Wang and Z. -X. Yang, "Semi-Supervised Self-Correcting Graph Neural Network for Intelligent Fault Diagnosis of Rotating Machinery," in IEEE Transactions on Instrumentation and Measurement, doi: 10.1109/TIM.2023.3314821. (JCR Q1, 中科院二区, 影响因子: 5.6)
[5] H. Chen, X. -B. Wang and Z. -X. Yang, "A Novel Rotating Machinery Fault Diagnosis System Using Ensemble Learning Capsule Autoencoder," in IEEE Sensors Journal, vol. 24, no. 1, pp. 1018-1027, 1 Jan.1, 2024. (JCR Q1, 中科院二区Top, 影响因子: 4.3)
[6] Chen, Hao, et al. "Privacy-preserving intelligent fault diagnostics for wind turbine clusters using federated stacked capsule autoencoder." Expert Systems with Applications 254 (2024): 124256. (JCR Q1, 中科院一区Top, 影响因子: 8.5)
[7] H. Chen, X. -B. Wang, J. -m. Li and Z. -X. Yang, "Dynamic Focusing Network for Semisupervised Mechanical Fault Diagnosis of Rotating Machinery," in IEEE Transactions on Industrial Informatics, vol. 20, no. 10, pp. 11575-11586, Oct. 2024, doi: 10.1109/TII.2024.3409443. (JCRQ1, 中科院一区Top,影响因子:12.3)
[8]Chen H , Li J M , Wang X B ,et al. Review of intelligent fault diagnosis for rotating machinery under imperfect data conditions[J].Expert Systems With Applications, 2025, 285.DOI:10.1016/j.eswa.2025.127726.(JCR Q1, 中科院一区Top, 影响因子: 8.5)
[9] H. Chen, X. -B. Wang and Z. -X. Yang, "Adaptive Semi-supervise Graph Neural Network for Fault Diagnosis of Tunnel Ventilation Systems," 2021 5th International Conference on System Reliability and Safety (ICSRS), 2021, pp. 53-57.
[10] Chen, H., X. -B. Wang and Z. -X. Yang, "Knowledge Graph for Fault diagnosis of Mechanical System," 2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS), Chengdu, China, 2022, pp. 795-799.
联系方式：
Email：2024051@wtu.edu.cn
orangechenh@outlook.com
