Soft sensors for product quality monitoring in debutanizer distillation columns
The paper deals with the design of neural based soft sensors to improve product quality
monitoring and control in a refinery by estimating the stabilized gasoline concentration (C5) …
monitoring and control in a refinery by estimating the stabilized gasoline concentration (C5) …
Soft analyzers for a sulfur recovery unit
This work deals with the design and implementation of soft sensors for a Sulfur Recovery
Unit (SRU) in a refinery. Soft sensors are mathematical models able to emulate the behavior …
Unit (SRU) in a refinery. Soft sensors are mathematical models able to emulate the behavior …
Development of soft sensors for isomerization process based on support vector machine regression and dynamic polynomial models
A novel data-driven soft sensor models for application in the refinery isomerization process
are presented. Soft sensor models based on support vector machine regression (SVM) and …
are presented. Soft sensor models based on support vector machine regression (SVM) and …
Optimal selection of soft sensor inputs for batch distillation columns using principal component analysis
E Zamprogna, M Barolo, DE Seborg - Journal of process control, 2005 - Elsevier
In this paper, a novel methodology based on principal component analysis (PCA) is
proposed to select the most suitable secondary process variables to be used as soft sensor …
proposed to select the most suitable secondary process variables to be used as soft sensor …
Development of soft sensor for neural network based control of distillation column
The present work is aimed at the design of Levenberg–Marquardt (LM) and adaptive linear
network (ADALINE) based soft sensors and their application in inferential control of a …
network (ADALINE) based soft sensors and their application in inferential control of a …
A nonlinear soft sensor based on multivariate smoothing procedure for quality estimation in distillation columns
S Park, C Han - Computers & Chemical Engineering, 2000 - Elsevier
An accurate on-line measurement of quality variables are essential for the successful
monitoring and control tasks in chemical process operations. However, due to the …
monitoring and control tasks in chemical process operations. However, due to the …
Soft-sensing estimation of plant effluent concentrations in a biological wastewater treatment plant using an optimal neural network
JF de Canete, P del Saz-Orozco, R Baratti… - Expert Systems with …, 2016 - Elsevier
Recent studies into the estimation and control of an activated sludge process (ASP) at a
wastewater treatment plant suggest that artificial-intelligence methods, such as neural …
wastewater treatment plant suggest that artificial-intelligence methods, such as neural …
Data-driven soft sensor approach for online quality prediction using state dependent parameter models
The goal of this paper is to design and implementation of a new data-driven soft sensor that
uses state dependent parameter (SDP) models to improve product quality monitoring. The …
uses state dependent parameter (SDP) models to improve product quality monitoring. The …
Soft sensor model for dynamic processes based on multichannel convolutional neural network
Soft sensors have been extensively used to predict the difficult-to-measure key quality
variables. The robust soft sensors should be able to sufficiently extract the local dynamic and …
variables. The robust soft sensors should be able to sufficiently extract the local dynamic and …
Comparison of soft-sensor design methods for industrial plants using small data sets
This paper analyzes a number of strategies that are devoted to improving the generalization
capabilities of neural-network-based soft sensors when only small data sets are available …
capabilities of neural-network-based soft sensors when only small data sets are available …