Biao Huang

Research interests

Publications

• Transfer Learning-Motivated Intelligent Fault Diagnosis Designs: A Survey, Insights, and Perspectives

  IEEE Transactions on Neural Networks and Learning Systems · 2023 · https://doi.org/10.1109/tnnls.2023.3290974

• Explainable Intelligent Fault Diagnosis for Nonlinear Dynamic Systems: From Unsupervised to Supervised Learning

  IEEE Transactions on Neural Networks and Learning Systems · 2022 · https://doi.org/10.1109/tnnls.2022.3201511

• Ecological risk assessment of heavy metals in sediments and water from the coastal areas of the Bohai Sea and the Yellow Sea

  Environment International · 2020 · https://doi.org/10.1016/j.envint.2020.105512

• Data-Driven Fault Diagnosis for Traction Systems in High-Speed Trains: A Survey, Challenges, and Perspectives

  IEEE Transactions on Intelligent Transportation Systems · 2020 · https://doi.org/10.1109/tits.2020.3029946

• A review On reinforcement learning: Introduction and applications in industrial process control

  Computers & Chemical Engineering · 2020 · https://doi.org/10.1016/j.compchemeng.2020.106886

• Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes

  Industrial & Engineering Chemistry Research · 2019 · https://doi.org/10.1021/acs.iecr.9b02391

• Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy

  IEEE Transactions on Industrial Informatics · 2019 · https://doi.org/10.1109/tii.2019.2938890

• Survey on the theoretical research and engineering applications of multivariate statistics process monitoring algorithms: 2008–2017

  The Canadian Journal of Chemical Engineering · 2018 · https://doi.org/10.1002/cjce.23249

• Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE

  IEEE Transactions on Industrial Informatics · 2018 · https://doi.org/10.1109/tii.2018.2809730

• Economics- and policy-driven organic carbon input enhancement dominates soil organic carbon accumulation in Chinese croplands

  Proceedings of the National Academy of Sciences · 2018 · https://doi.org/10.1073/pnas.1700292114

• Source identification of heavy metals in peri-urban agricultural soils of southeast China: An integrated approach

  Environmental Pollution · 2018 · https://doi.org/10.1016/j.envpol.2018.02.070

• Data Mining and Analytics in the Process Industry: The Role of Machine Learning

  IEEE Access · 2017 · https://doi.org/10.1109/access.2017.2756872

• A full‐condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis

  AIChE Journal · 2017 · https://doi.org/10.1002/aic.16048

• Geochemical baseline establishment and ecological risk evaluation of heavy metals in greenhouse soils from Dongtai, China

  Ecological Indicators · 2016 · https://doi.org/10.1016/j.ecolind.2016.08.037

• Semisupervised JITL Framework for Nonlinear Industrial Soft Sensing Based on Locally Semisupervised Weighted PCR

  IEEE Transactions on Industrial Informatics · 2016 · https://doi.org/10.1109/tii.2016.2610839

• Slow feature analysis for monitoring and diagnosis of control performance

  Journal of Process Control · 2016 · https://doi.org/10.1016/j.jprocont.2015.12.004

• Performance-Driven Distributed PCA Process Monitoring Based on Fault-Relevant Variable Selection and Bayesian Inference

  IEEE Transactions on Industrial Electronics · 2015 · https://doi.org/10.1109/tie.2015.2466557

• Design of inferential sensors in the process industry: A review of Bayesian methods

  Journal of Process Control · 2013 · https://doi.org/10.1016/j.jprocont.2013.05.007

• Model Predictive Control

  Journal of Control Science and Engineering · 2012 · https://doi.org/10.1155/2012/240898

• Evaluating soil quality indices in an agricultural region of Jiangsu Province, China

  Geoderma · 2009 · https://doi.org/10.1016/j.geoderma.2008.12.015

• Subspace method aided data-driven design of fault detection and isolation systems

  Journal of Process Control · 2009 · https://doi.org/10.1016/j.jprocont.2009.07.005

• Dynamic Modeling, Predictive Control and Performance Monitoring: A Data-driven Subspace Approach

  Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) · 2008 · https://doi.org/10.1007/978-1-84800-233-3

• A new method for stabilization of networked control systems with random delays

  IEEE Transactions on Automatic Control · 2005 · https://doi.org/10.1109/tac.2005.852550

• Closed-loop subspace identification: an orthogonal projection approach

  Journal of Process Control · 2004 · https://doi.org/10.1016/j.jprocont.2004.04.007

• H∞ model reduction of Markovian jump linear systems

  Systems & Control Letters · 2003 · https://doi.org/10.1016/s0167-6911(03)00133-6

• A data driven subspace approach to predictive controller design

  Control Engineering Practice · 2003 · https://doi.org/10.1016/s0967-0661(02)00112-0

• Detection of multiple oscillations in control loops

  Journal of Process Control · 2002 · https://doi.org/10.1016/s0959-1524(02)00007-0

• Performance Assessment of Control Loops

  Advances in industrial control · 1999 · https://doi.org/10.1007/978-1-4471-0415-5

• Performance Assessment of Control Loops: Theory and Applications

  Medical Entomology and Zoology · 1999

• Good, bad or optimal? Performance assessment of multivariable processes

  Automatica · 1997 · https://doi.org/10.1016/s0005-1098(97)00017-4

Current projects

No projects listed.