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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chitralekha, S.B. Shah, S.L. |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Chemical and Materials Engineering, University of Alberta, Edmonton, T6G 2G6 Canada (Chitralekha, S.B.; Shah, S.L.) |
| Abstract | The field of soft sensor development has gained significant importance in the recent past with the development of efficient and easily employable computational tools for this purpose. The basic idea is to convert the information contained in the input-output data collected from the process into a mathematical model. Such a mathematical model can be used as a cost efficient substitute for hardware sensors. The Support Vector Regression (SVR) tool is one such computational tool that has recently received much attention in the system identification literature, especially because of its successes in building nonlinear blackbox models. In this work we demonstrate the application of SVR as an efficient and easy-to-use tool for developing soft sensors for nonlinear processes. In an industrial case study, we illustrate the development of a steady state Melt Index soft sensor for an industrial scale Ethylene Vinyl Acetate (EVA) polymer extrusion process using SVR. The SVR based soft sensor, valid over a wide range of melt indices, outperformed the existing nonlinear least squares based soft sensor in terms of lower prediction errors. Through a second case study, we demonstrate the application of SVR for developing soft sensors in the form of dynamic models for a laboratory scale twin screw polymer extrusion process. |
| Starting Page | 569 |
| Ending Page | 574 |
| File Size | 265239 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424480913 |
| e-ISBN | 9781424480920 |
| DOI | 10.1109/MED.2010.5547730 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-23 |
| Publisher Place | Morocco |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Temperature measurement Support vector machines Training Soft sensor Laboratories Support Vector Regression Polymer extrusion System identification Mathematical model Polymers Kernel |
| Content Type | Text |
| Resource Type | Article |
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