​贺彦林

时间:2020-03-31浏览:41219

贺彦林(Yan-Lin He):教授 博士生导师 自动化系系主任

20166月获工学博士(控制科学与工程)20195月入选北京化工大学青年英才百人计划现任北京自动化学会理事、中国自动化学会应用专委会委员中国自动化学会数据驱动控制、学习与优化专业委员会委员中国人工智能学会不确定人工智能专委会委员,中国自动化学会青年工作委员会委员,中国化工学会信息技术应用专业委员会青年委员等。近五年,以第一作者/通信作者在IEEE Transactions 汇刊《IEEE Trans. on Ind. Inform.》《IEEE T. Contr. Syst. T.》、《IEEE T. Instrum. Meas.》、《IEEE T. Reliab.,中国自动化学会推荐A/B刊,IFAC会刊和化工类国际顶级期刊等权威期刊发表SCI论文70余篇;专利授权10申请专利20主持国家自然科学基金青年项目面上项目获北京市科协2020-2022年度青年人才托举计划2018年北京自动化学会青年科技创新人才,入选全球前2%顶尖科学家榜单等。

研究方向:计算智能、系统建模与优化、软测量、故障诊断、机器学习等。

教学课程Teaching courses

课程名称

面向对象

人工智能基础

本科生

人工智能及应用

本科生

高端装备与自动化专业导论课

本科生

模式识别与机器学习

本科生

智能制造系统

研究生

系统工程理论

研究生

Neural Network Technology

留学生

主持、参与的主要科研项目 Research Projects

项目名称

项目来源

复杂化工过程故障诊断及其根源分析关键技术研究

国家自然科学基金面上项目

基于VSG ELM 的复杂石化过程智能建模方法研究

国家自然科学基金青年项目

工控系统安全主动防御机制及体系研究

国家重点研发计划项目

复杂石化过程智能化建模与诊断

智能过程系统工程教育部工程研究中心基地创新项目

面向故障诊断的动态时间维度信息挖掘理论研究

自由探索项目

I-CWP M线效率模块开发

企业横向项目

10代表论文Research Papers

[1]P. -F. Wang, Q. -X. Zhu and Yan-Lin He, Novel Multiscale Trend Decomposition LSTM Based on Feature Selection for Industrial Soft Sensing, in IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2024.3444896.

[2]Yan-Lin He, L. Chen and Q. -X. Zhu, Quality Regularization-Based Semisupervised Adversarial Transfer Model With Unlabeled Data for Industrial Soft Sensing, in IEEE Transactions on Industrial Informatics, vol. 20, no. 2, pp. 1190-1197, Feb. 2024, doi: 10.1109/TII.2023.3272690.

[3]Yan-Lin He, J. -T. Liang, Y. Tian and Q. -X. Zhu, Novel Schur Decomposition Orthogonal Exponential DLPP With Mixture Distance for Fault Diagnosis, in IEEE Transactions on Industrial Informatics, vol. 20, no. 4, pp. 5601-5608, April 2024, doi: 10.1109/TII.2023.3336766.

[4]Yan-Lin He, P. -F. Wang and Q. -X. Zhu, Improved Bi-LSTM With Distributed Nonlinear Extensions and Parallel Inputs for Soft Sensing, in IEEE Transactions on Industrial Informatics, vol. 20, no. 3, pp. 3748-3755, March 2024, doi: 10.1109/TII.2023.3313631.

[5]Yan-Lin He, S. -H. Lv, Q. -X. Zhu and S. Lu, Novel Multiattribute Space-Based LSTM for Industrial Soft Sensor Applications, in IEEE Transactions on Industrial Informatics, vol. 20, no. 3, pp. 4745-4752, March 2024, doi: 10.1109/TII.2023.3316289.

[6]L. Chen, Y. Xu, Q. -X. Zhu and Yan-Lin He*, Adaptive Multi-Head Self-Attention Based Supervised VAE for Industrial Soft Sensing With Missing Data, in IEEE Transactions on Automation Science and Engineering, vol. 21, no. 3, pp. 3564-3575, July 2024, doi: 10.1109/TASE.2023.3281336.

[7]Yan-Lin He, X. -Y. Li, Y. Xu, Q. -X. Zhu and S. Lu, Novel Distributed GRUs Based on Hybrid Self-Attention Mechanism for Dynamic Soft Sensing, in IEEE Transactions on Automation Science and Engineering, doi: 10.1109/TASE.2023.3309339.

[8]Yan-Lin He, L. Chen, Y. Xu, Q. -X. Zhu and S. Lu, A New Distributed Echo State Network Integrated With an Auto-Encoder for Dynamic Soft Sensing, in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-8, 2023, Art no. 2500308, doi: 10.1109/TIM.2022.3228278.

[9]He Yan-Lin, K. Li, L. -L. Liang, Y. Xu and Q. -X. Zhu, Novel Discriminant Locality Preserving Projection Integrated With Monte Carlo Sampling for Fault Diagnosis, in IEEE Transactions on Reliability, vol. 72, no. 1, pp. 166-176, March 2023, doi: 10.1109/TR.2021.3115108.

[10]He Yan-Lin, Li Kun, Zhang Ning, Xu Yuan, Zhu Qun-Xiong, Fault Diagnosis Using Improved Discrimination Locality Preserving Projections Integrated With Sparse Autoencoder, IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-8, 2021.

科研成果展示

 

基于计算智能的工业软测量应用

 

 

工业过程数据特征处理

 

  

复杂流程工业故障数据特征信息分析和诊断