Jain, P. ; Rahman, I. ; Kulkarni, B. D. (2007) Development of a soft sensor for a batch distillation column using support vector regression techniques Chemical Engineering Research and Design, 85 (2). pp. 283-287. ISSN 0263-8762
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Official URL: http://linkinghub.elsevier.com/retrieve/pii/S02638...
Related URL: http://dx.doi.org/10.1205/cherd05026
Abstract
A support vector regression (SVR)-based model is developed for a batch distillation process in order to estimate the product compositions from temperature measurements. Kernel function such as linear, polynomial and RBF are employed for SVR modelling. The original process data was generated by simulating the batch distillation process, varying the initial feed composition and boilup rate from batch to batch. Within each batch reflux ratio was also randomly changed to represent the true dynamics of the batch distillation. The results show the potential of the method for developing softsensor for chemical processes.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Institution of Chemical Engineers. |
| Keywords: | Batch Distillation; Soft Sensor; Composition Estimation; Support Vector Regression |
| ID Code: | 17341 |
| Deposited On: | 16 Nov 2010 08:08 |
| Last Modified: | 06 Jun 2011 08:53 |
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