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Multi-Scale PLS Modeling for Industrial Process Monitoring
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 26 - Number 6 |
| Year of Publication: 2011 |
| Authors: Mohammad Sadegh Emami Roodbali, Mehdi Shahbazian |
10.5120/3107-4266
|
Mohammad Sadegh Emami Roodbali, Mehdi Shahbazian . Multi-Scale PLS Modeling for Industrial Process Monitoring. International Journal of Computer Applications. 26, 6 ( July 2011), 26-33. DOI=10.5120/3107-4266
Abstract
In the process monitoring procedure, Data-driven (statistical) methods usually rely on the process measurements. In most industrial process this measurements has a multi-scale substance in time and frequency. Therefore the statistical methods which are proper for one scale may not be able to detect events at several scales. A Multi-Scale Partial Least Squares (MSPLS) algorithm consists of Wavelet Transforms for extracting multi-scale nature of measurements and Partial Least Squares (PLS) as a popular technique of statistical monitoring methods. In this paper the MSPLS algorithm is applied for monitoring of the Tennessee Eastman Process as a benchmark. To show the advantages of MSPLS, its process monitoring performance is compared with the standard PLS and is proved that MSPLS can be a more efficient technique than standard PLS for fault detection in industrial processes.
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