Soft Sensors to Monitoring a Multivariate Nonlinear Process Using Neural Networks

Journal of control, automation and electrical systems

article

Monteiro, Nathalia Arthur Brunet¹  da Silva, Jaidilson Jó¹  da Rocha Neto, José Sérgio¹ 

[1] Department of Electrical Engineering, Federal University of Campina Grande (UFCG)

关键词: Monitoring;    Modeling;    Neural networks;    Soft sensor;    System identification;   

DOI  :  10.1007/s40313-018-00426-x

学科分类：自动化工程

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY