教科研及 成果简介 | 个人概况： 丁逸飞，工学博士，副教授，硕士生导师，现任苏州工学院机械工程学院教师。2023年于东南大学获得博士学位，2022.10-2023.10曾赴加拿大多伦多大学联合培养。主要从事工业人工智能与大数据分析、机电设备智能运维与健康管理等方向研究。主持和参与多项国家自然科学基金、江苏省自然科学基金等项目。入选斯坦福大学“全球前2%顶尖科学家”2024年度榜单，ScholarGPS全球高影响力学者Top 0.5%。 截至目前，共计发表学术论文30余篇，申请和授权国家发明专利20余项。其中 近5年以第一作者发表SCI论文13篇，EI论文2篇；根据中科院2025升级版分区有：中科院一区8篇、二区5篇；其中，包含IEEE/ASME Trans. 系列（TII、TMECH、TIM）论文5篇、MSSP论文1篇；ESI热点、高被引论文（第一作者）3篇。Google Scholar引用2500余次，h指数21。 相关链接： 谷歌学术：https://scholar.google.com/citations?user=6UNuAmgAAAAJ&hl ResearchGate：https://www.researchgate.net/profile/Yifei-Ding-3 主要科研项目： [1]. 国家自然科学基金青年项目，融合领域知识泛化与测试时自适应的海上风电轴承寿命预测研究（No.52505610），2026.01-2028.12，主持。 [2]. 江苏省自然科学基金青年项目，时变耦合激励下自适应持续学习驱动的电主轴轴承寿命预测研究，2025.07-2028.06，主持。 [3]. 江苏省高等学校基础科学（自然科学）研究面上项目，基于在线增量自适应的电主轴轴承跨域协同寿命预测研究，2025.07-2027.07，主持。 [4]. 江苏省普通高校研究生科研创新计划项目，基于迁移学习的滚动轴承剩余寿命预测方法及应用研究（KYCX21_0082），2021.06-2022.09，主持。 代表性学术成果： [1]. Ding Y (丁逸飞), Jia M *, Zhuang J, et al. Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions[J]. Reliability Engineering & System Safety, 2023, 230: 108890. (中科院1区, TOP期刊, IF: 11.0, ESI热点论文) [2]. Ding Y (丁逸飞), Jia M *, Miao Q, et al. A novel time–frequency Transformer based on self–attention mechanism and its application in fault diagnosis of rolling bearings[J]. Mechanical Systems and Signal Processing, 2022, 168: 108616. (中科院1区, TOP期刊, IF: 8.9, ESI高被引论文) [3]. Ding Y (丁逸飞), Zhuang J, Ding P, et al. Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings[J]. Reliability Engineering & System Safety, 2022, 218: 108126. (中科院1区, TOP期刊, IF: 11.0, ESI高被引论文) [4]. Ding Y (丁逸飞), Jia M *, Miao Q, et al. Remaining useful life estimation using deep metric transfer learning for kernel regression[J]. Reliability Engineering & System Safety, 2021, 212. (中科院1区, TOP期刊, IF: 11.0) [5]. Ding Y (丁逸飞), Jia M *, Cao Y, et al. Unsupervised Fault Detection With Deep One-Class Classification and Manifold Distribution Alignment[J]. IEEE Transactions on Industrial Informatics, 2024, 20(2): 1313-1323. (中科院1区, TOP期刊, IF: 9.9) [6]. Ding Y (丁逸飞*), Cao Y, Jia M, et al. Deep temporal–spectral domain adaptation for bearing fault diagnosis[J]. Knowledge-Based Systems, 2024, 299: 111999. (中科院1区, TOP期刊, IF: 7.6) [7]. Ding Y (丁逸飞), Jia M *, Cao Y, et al. Domain generalization via adversarial out-domain augmentation for remaining useful life prediction of bearings under unseen conditions[J]. Knowledge-Based Systems, 2023, 261: 110199. (中科院1区, TOP期刊, IF: 7.6) [8]. Ding Y (丁逸飞), Ding P, Zhao X, et al. Transfer Learning for Remaining Useful Life Prediction Across Operating Conditions Based on Multisource Domain Adaptation[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(5): 4143-4152. (中科院1区, TOP期刊, IF: 7.3) [9]. Ding Y (丁逸飞), Jia M (贾民平*), Zhuang J (庄集超), et al. Deep imbalanced regression using cost-sensitive learning and deep feature transfer for bearing remaining useful life estimation[J]. Applied Soft Computing, 2022, 127: 109271. (中科院2区, TOP期刊, IF: 6.6) [10]. Ding Y (丁逸飞), Jia M *, Zhao X, et al. Joint optimization of degradation assessment and remaining useful life prediction for bearings with temporal convolutional auto-encoder[J]. ISA Transactions, 2024, 146: 451-462. (中科院2区, TOP期刊, IF: 6.5) [11]. Ding Y (丁逸飞), Jia M *, Cao Y. Remaining Useful Life Estimation Under Multiple Operating Conditions via Deep Subdomain Adaptation[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-11. (中科院2区, TOP期刊, IF: 5.9) [12]. Ding Y (丁逸飞), Ding P, Jia M *. A Novel Remaining Useful Life Prediction Method of Rolling Bearings Based on Deep Transfer Auto-Encoder[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-12. (中科院2区, TOP期刊, IF: 5.9) [13]. Ding Y (丁逸飞), Jia M *. Convolutional Transformer: An Enhanced Attention Mechanism Architecture for Remaining Useful Life Estimation of Bearings[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1-10. (中科院2区, TOP期刊, IF: 5.9) [14]. Ding Y (丁逸飞), Jia M *. Cross-Domain Fault Diagnosis for Rotating Machines with Multi-Scale Domain Adaptation[C]//2022 Global Reliability and Prognostics and Health Management (PHM-Yantai). 2022: 1-6. (EI, 会议最佳论文Best Paper Award) [15]. Ding Y (丁逸飞), Jia M *. A Convolutional Transformer Architecture for Remaining Useful Life Estimation[C]//2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing). 2021: 1-7. (EI) 学术兼职： § 江苏省工程图学学会第十届理事、青年委员 § 中国机械工程学会高级会员 § 担任IEEE TNNLS、IEEE TSMC、IEEE TIE、IEEE TII、MSSP、KBS、ESWA、EAAI、RESS、IEEE/ASME TMECH、Pattern Recognition、Advanced Engineering Informatics、Computers & Industrial Engineering、 Applied Energy等SCI一区期刊审稿人。 |
