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