Title :
FPGA based soft sensor for the estimation of the kerosene freezing point
Author :
Caponetto, R. ; Dongola, G. ; Gallo, A. ; Xibilia, Maria Gabriella
Author_Institution :
Eng. Fac., Univ. of Catania, Catania, Italy
Abstract :
A new strategy to realize an FPGA implementation of a soft sensor for an industrial process is proposed. In order to cope with the problem of small data sets in the identification of a non linear model the proposed approach is based on the integration of bootstrap re-sampling, noise injection and stacked neural networks (NNs), using the Principal Component Analysis (PCA). The aggregated final NN-PCA system has been implemented on Field Programmable Gate Array (FPGA). The proposed method has been applied to develop a soft sensor for the estimation of the freezing point of kerosene in an atmospheric distillation unit (topping) working in a refinery in Sicily, Italy.
Keywords :
field programmable gate arrays; neural nets; petroleum; principal component analysis; FPGA; field programmable gate array; kerosene freezing point; neural network; neural networks; pricipal component analysis; soft sensor; Data engineering; Databases; Delay; Field programmable gate arrays; Laboratories; Monitoring; Neural networks; Principal component analysis; Size measurement; Training data; FPGA Implementation; Neural Network; Pricipal Component Analysis; Soft-Sensors;
Conference_Titel :
Industrial Embedded Systems, 2009. SIES '09. IEEE International Symposium on
Conference_Location :
Lausanne
Print_ISBN :
978-1-4244-4109-9
Electronic_ISBN :
978-1-4244-4110-5
DOI :
10.1109/SIES.2009.5196219
