In the paper a Soft Sensor design strategy for an industrial process, via neural NMA model, is described. A general design strategy, based on the automatic selection of regressors of a NAM model is proposed. It is based on the minimization of the cost function of a Gath Geva clustering algorithm. The obtained soft sensor will be implemented in a refinery in order to replace the measurement device during maintenance to guarantee continuity in the monitoring and control of the plant.
Soft Sensor design for a Sulfur Recovery Unit using a clustering based approach
XIBILIA, Maria Gabriella
2008-01-01
Abstract
In the paper a Soft Sensor design strategy for an industrial process, via neural NMA model, is described. A general design strategy, based on the automatic selection of regressors of a NAM model is proposed. It is based on the minimization of the cost function of a Gath Geva clustering algorithm. The obtained soft sensor will be implemented in a refinery in order to replace the measurement device during maintenance to guarantee continuity in the monitoring and control of the plant.File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
