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Soft Sensors to Monitoring a Multivariate Nonlinear Process Using Neural Networks

  • Nathalia Arthur Brunet Monteiro
  • Jaidilson Jó da Silva
  • José Sérgio da Rocha Neto
Article
  • 54 Downloads

Abstract

In general, industrial processes have a multivariable nature, with multiple inputs and multiple outputs. Such systems are more difficult to monitor and control due to interactions between the input and output variables. Focusing on these issues, the development of soft sensors to monitor multivariate nonlinear processes using neural networks is proposed. Experiments were performed to monitor the pressure and flow values on an experimental platform (fluid transport system) using developed soft sensors. With the monitoring using soft sensor, it is possible to make processes more reliable, with better performance and with less difficulty in detecting and solving possible failures.

Keywords

Monitoring Modeling Neural networks Soft sensor System identification 

Notes

Acknowledgements

The authors would like to thank CNPq and Copele-DEE for financial support.

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Copyright information

© Brazilian Society for Automatics--SBA 2018

Authors and Affiliations

  1. 1.Department of Electrical EngineeringFederal University of Campina Grande (UFCG)Campina GrandeBrazil

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