DocumentCode :
702131
Title :
Inferential sensor for the olive oil industry
Author :
Bordons, Carlos ; Zafra, Manuel L.
Author_Institution :
Depto. de Ingeniería de Sistemas y Automática, Escuela Superior de Ingenieros, Camino de los Descubrimientos s/n, 41092-Sevilla (Spain)
fYear :
2003
fDate :
1-4 Sept. 2003
Firstpage :
1940
Lastpage :
1946
Abstract :
This paper shows an inferential sensor that has been developed to be used in the olive oil industry. This sensor has been designed to measure two variables that appear in the elaboration of olive oil in a mill which are very difficult to be measured on line by a physical sensor. The knowledge of these variables on line is crucial for the optimal operation of the process, since they provide the state of the plant, allowing the development of a control strategy that can improve the quality and yield of the product. This sensor measures variables that in other case should come form laboratory analysis with large processing delays or from very expensive and difficult to use on line analysers. The sensor has been devised based upon artificial Neural Networks (NN) and has been implemented as a routine running on a Programmable Logic Controller (PLC) and successfully tested on a real plant.
Keywords :
Artificial neural networks; Delays; Estimation; Moisture; Temperature measurement; Training; Food Industry; Inferential Sensors; Neural Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
European Control Conference (ECC), 2003
Conference_Location :
Cambridge, UK
Print_ISBN :
978-3-9524173-7-9
Type :
conf
Filename :
7085250
Link To Document :
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