科研项目: [1]基于数字孪生技术的猪肉智慧生产多尺度协同智能分析平台研发与示范 (2022YFG0046),四川省科技厅2022年重点研发计划,2022.01-2023.12,100万,主持. [2]电动汽车变速器故障辨识的多尺度动态深度神经网络模型研究 (cstc2020jcyj-msxmX0683),重庆市自然科学基金面上项目,2020.07.01-2023.06.30,10万,主持. [3]基于高维异构数据的电动汽车变速器早期故障识别方法研究 (61903055),国家自然科学基金青年科学基金项目,2020.1-2022.12,24万,主持. [4]组织智慧安全校园技术研讨会,横向项目(杭州海康威视数字技术股 有限公司),2019.09-2019.12,20万,主持. [5]智慧电子政务办公平台设计方案技术服务,横向项目(中国科学院重庆 绿色智能技术研究院),2019.11-2019.12,10万,主持. [6]基于大数据的城市桥梁健康分析与诊断方法研究(KJQN201901507),重 庆市教委科学技术研究项目,2019.9-2021.9,4万,主持. [7]数字设备监测系统技术开发,横向项目(重科指挥能源研究院(重庆)有限 公司),2019.04-2019.06,5万,主持. [8]强噪声下电动汽车变速器齿轮箱故障识别方法研究(KJQN201801504), 重庆市教委科学技术研究项目,2018.9-2020.9,5万,主持. [9]汽车变速器齿轮箱安全智能辅助系统关键技术的研发(cstc2018jscx- msybX0318),重庆市技术创新与应用示范项目(社会民生类一般项目),2018.01-2020.12,10万,主持. [10]基于声场特性的电动汽车变速箱齿轮故障识别方法研究(Xm2017103),重 庆市博士后科研项目特别资助项目,2017.09-2018.09,5万,主持. [11]输气管道微泄漏音波信号机理与识别方法研究(cstc2017jcyjAX0221),重 庆市科委基础科学与前沿技术研究项目,2017.5-2020.4,5万,主持. [12]天然气输送管道接口处微泄漏预警系统关键技术研发(chongqing-0007- 2016AQ),国家安全生产监督管理总局安全生产重大事故防治关键技术科技项目,2016.01-2017.12,15万元,主持. [13]区域和省级安全生产大数据预警平台建设方案研究(C0AWS2015Y-003), 国家安全生产监督管理总局,2015.03-2015.09,1.5万元,主持. [14]基于深度卷积神经网络的加气站天然气管道微泄漏检测方法研究 (KJ1501305),重庆市教委科学技术研究项目,2015.7-2017.6,3万,主持. |
代表性成果: [1]Jie Li, Song Liu, Haibo He, Lusi Li. A novel framework for gear safety factor prediction. IEEE Transactions on Industrial Informatics, 2019, 15(4) : 1998-2007. (IF:7.53, SCI :000467095500015,JCR一区). [2]Jie Li, Haibo He, Lusi Li, Guorong Chen. A novel generative model with bounded-GAN for reliability classification of gear safety. IEEE Transactions on Industrial Electronics, 2019, 66(11):8772-8781 (IF:7.05, SCI:000474570200046, JCR一区). [3]Jie Li, Hongli He, Haibo He, Lusi Li, Yi Xiang. An end-to-end framework with multisource monitoring data for bridge health anomaly identification. IEEE Transactions on Instrumentation and Measurement, 2020, 70. (IF:3.067, SCI:000591842200073, JCR一区) [4]Jie Li, Haibo He, Lusi Li. CGAN-MBL for reliability assessment with imbalanced transmission gear data. IEEE Transactions on Instrumentation and Measurement,2019, 68(9):3137-3183 (IF:3.067, SCI:000480651000013, JCR一区). [5]Jie Li, Haibo He. Information Generative Bayesian Adversarial Networks (IGBAN) : A representation learning model for transmission gear parameters. IEEE/ASME Transactions on Mechatronics, 2019, 24(5) : 1998-2007. (IF:4.943, SCI:000493174900009,JCR一区). [6]Jie Li, Boyu Zhao, Kai Wu, Zhicheng Dong, Xuerui Zhang, and Zhihao Zheng. A representation generation approach of transmission gear based on conditional generative adversarial network. Actuators, 2021, 10(5):86. (IF: 1.957, SCI:00065329080001.) [7]Jie Li, Qinlin Huang, Siyu Ren, et al. A novel medical text classification model with Kalman filter for clinical decision making[J].Biomedical Signal Processing and Control, 2023, 82:104503. [8]Jie Li, Yifan Wang, Chongju Luo, Weixi Zhou and Zhicheng Dong.CNN- LDNF: An Image Feature Representation Approach with Multi-Space Mapping. International Journal of Machine Learning and Cybernetics.2022, 58. [9]Ping Wan, Hongli He, Ling Guo, Jiancheng Yang and Jie Li (通讯作者). InfoGAN-MSF: a data-augmenting approach for correlative bridge monitoring factors. Measurement Science and Technology, 2021, 32,114008. (IF: 2.036, SCI:000685770500001.) [10] Ping Wan, Ling Guo, Ming Li, Min Gao, Hongping Zhang, and Jie Li (通讯作者). A backbone-edge feature extraction method for varied industrial parts. International Journal of System Control and Information Processing, 2022. |