范伟(邮箱：wfan@just.edu.cn)，男，博士，江苏科技大学能源与动力学院讲师（动力工程及工程热物理、能源动力硕导），研究方向为工业过程状态监测及故障诊断，智慧电站及电力大数据分析，大型工业过程系统特性建模，机器学习理论研究。美国化学学会（ACS）和电气电子工程师学会（IEEE）会员，承担IEEE Transactions on Industrial Informatics, IEEE Transactions on Control Systems Technology, IEEE Sensors Journal,Control Engineering Practice, The Canadian Journal of Chemical Engineering等国际期刊的审稿工作。
欢迎对机器学习算法和工业过程数据驱动建模感兴趣的同学加入课题组！
部分论文发表情况：
[10] Wei Fan et al. A Holistic Process Monitoring Model Based on Nonstationary Probabilistic Predictable Feature Analysis. In preparation, 2025.
[9] Wei Fan et al. Concurrent Quality and Process Monitoring with A Probabilistic Sparse Nonlinear Dynamic Method. Submitted to Control Engineering Practice, 2025.
[8] Wei Fan et al. Semi-supervised probabilistic predictable feature analysis for concurrent process-quality monitoring of a thermal power plant, IEEE Transactions on Instrumentation and Measurement, 2025, 74:1-12.
[7] Wei Fan; Yinfeng Jin; Cong Yu; Yongzan Zhou. PSINDy: Probabilistic sparse identification of nonlinear dynamics for temporal process modelling and fault detection, Journal of the Taiwan Institute of Chemical Engineers, 2023, 153: 105238.
[6] Wei Fan; Qinqin Zhu; Shaojun Ren; Liang Zhang; Fengqi Si. Dynamic Probabilistic Predictable Feature Analysis for Multivariate Temporal Process Monitoring, IEEE Transactions on Control Systems Technology, 2022, 30(6): 1-12.
[5] Wei Fan; Qinqin Zhu; Shaojun Ren; Liang Zhang; Fengqi Si. Robust probabilistic predictable feature analysis and its application for dynamic process monitoring, Journal of Process Control, 2022, 112: 21-35.
[4] Wei Fan; Shaojun Ren; Cong Yu; Haiquan Yu; Peng Wang; Fengqi Si. A mixture of probabilistic predictable feature analysis for multi-mode dynamic process monitoring, Journal of the Taiwan Institute of Chemical Engineers, 2022, 143: 104635.
[3] Wei Fan; Qinqin Zhu; Shaojun Ren; Bo Xu; Fengqi Si. Multivariate temporal process monitoring with graph‐based predictable feature analysis, The Canadian Journal of Chemical Engineering, 2022, 101(2): 909-924.
[2] Wei Fan; Shaojun Ren; Qinqin Zhu; Zhijun Jia; Delong Bai; Fengqi Si. A Novel Multi-Mode Bayesian Method for the Process Monitoring and Fault Diagnosis of Coal Mills, IEEE Access, 2021, 9: 22914-22926.
[1] Wei Fan; Fengqi Si; Shaojun Ren; Cong Yu; Yanfeng Cui; Peng Wang. Integration of continuous restricted Boltzmann machine and SVR in NOx emissions prediction of a tangential firing boiler, Chemometrics and Intelligent Laboratory Systems, 2019, 195: 103870.
其他论文：
[8] Zixuan Lin*,Jiao Wang, Wei Fan# et al. Dynamic NOx emission prediction for a 660MW super-critical coal-fired boiler using integrated time series network with adaptive filtering and deep learning. Submitted to Neurocomputing, 2025.
[7] Ziwei Wang*, Wei Fan# et al. Dynamic prediction of NOx emissions based on Kolmogorov-Arnold Network integrated deep learning method for a 660MW coal-fired boiler. Submitted to Energy, 2025.
[6] Ziwei Wang*, Wei Fan# et al. Forecast of NOx emissions for a 660MW coal-fired boiler with deep gradient boosting decision tree considering multiple operating modes. ACS Omega, 2024, 9(46): 45884-45897.
[5] Yanfeng Cui,Wei Fan#, Yongzan Zhou. Dimensionality Reducing Gaussian Mixture-based Reconstruction for Fault Detection in Multi-mode Industrial Processes. The Canadian Journal of Chemical Engineering, 2024, 102(12): 4267-4280.
[4] Ying Liu; Jianxin Zhou; Wei Fan#. A novel robust dynamic method for NOx emissions prediction in a thermal power plant, The Canadian Journal of Chemical Engineering, 2023, 101(5): 2391-2402.
[3] Peng Wang, Fengqi Si, Wei Fan, Shaojun Ren. Data Enhancement for Data-Driven Modeling in Power Plants Based on a Conditional Variational-Adversarial Generative Network, Industrial & Engineering Chemistry Research, 2021, 60(24): 8829-8843.
[2] Yukun Zhu*, Cong Yu, Wei Fan, Haiquan Yu, Wei Jin, Shuo Chen, & Xia Liu. A novel NOx emission prediction model for multimodal operational utility boilers considering local features and prior knowledge. Energy, 2023, 128128.
[1] Shuo Chen, Cong Yu, Yukun Zhu, Wei Fan, Haiquan Yu, Tihua Zhang. NOx formation model for utility boilers using robust two-step steady-state detection and multimodal residual convolutional auto-encoder, Journal of the Taiwan Institute of Chemical Engineers, 2024, 105252.
注：上标“*”为指导的学生,标注“#”为本人通讯。
科研项目：
[1] 企业项目：“互联网+民用爆炸物品生产及仓储智能化安全监控系统”技术开发，主持，2023.07；
[2] 企业项目： 厂级循环水系统优化运行在线指导系统研究与应用，主持，2023.10；
[3] 企业项目： 工业过程数据采集系统开发，主持，2023.12；
[4] 企业项目： 非稳动态过程性能建模及状态监测技术开发，主持，2024.01；
[5] 企业项目： 面向工业过程的数据采集协议转换开发，主持，2024.06；
专利申请：
[4]范伟;王梓维;丁甲博;李钰;吕宁;王蛟;一种基于半监督概率可预测特征模型的火电机组中速磨煤机异常监测方法,发明专利，申请号：202410592748.9
[3]范伟;刘颖;于海泉;李钰;吕宁;一种等离子喷涂水泵外壳材料及其制备方法与应用，发明专利，申请号：202311803213.3
[2]李树洲;司风琪;张贝;范伟;喻聪;江晓明;基于多源信息融合技术的燃煤锅炉SCR催化剂寿命评价方法,发明专利, CN201710131479.6
[1]朱誉;周建新;范伟;司风琪;谭力强 ;一种基于新型自组织格栅动态库的负荷分配方法,发明专利，CN201710807936.9
指导学生：
4.指导本科生获2025美国大学生数学建模竞赛二等奖；
3.王梓维-2021级本科生（获批2024年度大学生创新创业训练计划国家级项目，发表SCI论文1篇，保研至西安交通大学）；
2.李昊晨-2023级硕士（联合指导）；
1.徐顾鑫-2021级硕士（联合指导）；
