DocumentCode :
2679447
Title :
On Line Estimation of Composition Using Software Sensor in Batch Distillation Operation
Author :
Patil, S.V. ; Mankar, R.B. ; Mahadik, M.M.
fYear :
2011
fDate :
20-22 July 2011
Firstpage :
1
Lastpage :
6
Abstract :
This work addresses the design of a software sensor using GRNN model for predictions of product compositions. Product composition in distillation column is a function of operating temperature, heat load, reflux ratio and time duration. Design guidelines using GRNN model has been presented for modeling of batch distillation column. GRNN model is used to correlate input and output data and it has potential to approximate non linear input output relationship efficiently. Model is constructed exclusively from historic process input output data, by undergoing on line training. GRNN formulation and network training being one-step process. The experimental results of compositions found to agree well with model-simulated results.
Keywords :
batch processing (industrial); chemical engineering; chemical industry; distillation equipment; production engineering computing; GRNN model; batch distillation operation; chemical industries; heat load; network training; operating temperature; product composition online estimation; reflux ratio; software sensor; time duration; Data models; Distillation equipment; Heating; Load modeling; Software; Temperature measurement; Valves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Process Automation, Control and Computing (PACC), 2011 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-61284-765-8
Type :
conf
DOI :
10.1109/PACC.2011.5978969
Filename :
5978969
Link To Document :
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