In this paper the problem of regressors selection in Virtual Instruments (VI) design is addressed. The VI is designed to replace the on line analyzer of a Sulfur Recovery Unit (SRU) of a large refinery located in Sicily during maintenance operations. It is designed by using nonlinear MA models implemented by a MLP neural network. The use of a set of cross-correlation functions, proposed by Billings and Voon to evaluate the performance of nonlinear models is used to select the regressors of the discrete-time NMA model by implementing an automatic regressor selection algorithm. The designed Soft Sensor has been implemented at the refinery to be tested on line. © 2007 IEEE.

Selection of regressors using correlation analysis to design a Virtual Instrument for an SRU of a refinery

Napoli Grazia;
2007

Abstract

In this paper the problem of regressors selection in Virtual Instruments (VI) design is addressed. The VI is designed to replace the on line analyzer of a Sulfur Recovery Unit (SRU) of a large refinery located in Sicily during maintenance operations. It is designed by using nonlinear MA models implemented by a MLP neural network. The use of a set of cross-correlation functions, proposed by Billings and Voon to evaluate the performance of nonlinear models is used to select the regressors of the discrete-time NMA model by implementing an automatic regressor selection algorithm. The designed Soft Sensor has been implemented at the refinery to be tested on line. © 2007 IEEE.
2007
Correlation analysis
Moving average models
Neural modelling
Refinery
Regressor selection
Virtual instruments
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/227750
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