Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research

This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial...

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Bibliographische Detailangaben
1. Verfasser: Shang, Chao (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Singapore : Springer Singapore , 2018.
Ausgabe:1st ed. 2018.
Schriftenreihe:Springer Theses, Recognizing Outstanding Ph.D. Research,
Schlagworte:
Quality control.
Reliability.
Industrial safety.
Manufactures.
Control engineering.
Statistics .
ISBN:9789811066771
ISSN:2190-5053
Online-Zugang: Volltext
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Inhaltsangabe:
  • Introduction
  • Concurrent monitoring of steady state and process dynamics with SFA
  • Online monitoring and diagnosis of control performance with SFA and contribution plots
  • Recursive SFA algorithm and adaptive monitoring system design
  • Probabilistic SFR model and its applications in dynamic quality prediction
  • Improved DPLS model with temporal smoothness and its applications in dynamic quality prediction
  • Nonlinear and dynamic soft sensing model based on Bayesian framework
  • Summary and open problems.

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