Industrial Process Modelling with Mechanical Frequency Spectrum Data

Jian Tang · Wen Yu

Aga 2020 · Cambridge Scholars Publishing

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511

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Different industries use data analytics and the process modelling technique successfully in a variety of ways. These popular intelligent approaches improve the quality and quantity of production. This book focuses on the technique of soft-sensing based on spectral data with multi-source high-dimensional mechanical frequency in order to assess difficult-to-measure process parameters.

The book will be of interest to researchers and professors working in data analytics, engineers and technicians who need a modelling method based on small sample data, and PhD students who need to solve modelling and control challenges in a practical way.

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Jian Tang is a Professor in the Faculty of Information Technology at Beijing University of Technology. His research interest is intelligent modelling and the control of complex industrial processes. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and has published more than 40 papers. He has published work in IEEE Transactions on Industrial Informatics, IEEE Transaction on Automation Science and Engineering, Mechanical Systems and Signal Processing on selective information fusion modeling using frequency spectrum data.

Wen Yu received his MS and PhD in Electrical Engineering from Northeastern University, Shenyang, China, in 1992 and 1995, respectively. From 1995 to 1996, he served as a Lecturer in the Department of Automatic Control at the same university, and, since 1996, has been with the Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional, Mexico, where he is currently a Professor with the Departamento de Control Automatico. He serves as Associate Editor of IEEE Transactions on Cybernetics, Neurocomputing, and Journal of Intelligent and Fuzzy Systems, and is a member of the Mexican Academy of Sciences.

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