International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 26 - Issue 6 |
Published: July 2011 |
Authors: Mohammad Sadegh Emami Roodbali, Mehdi Shahbazian |
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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
@article{ 10.5120/3107-4266, author = { Mohammad Sadegh Emami Roodbali,Mehdi Shahbazian }, title = { Multi-Scale PLS Modeling for Industrial Process Monitoring }, journal = { International Journal of Computer Applications }, year = { 2011 }, volume = { 26 }, number = { 6 }, pages = { 26-33 }, doi = { 10.5120/3107-4266 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2011 %A Mohammad Sadegh Emami Roodbali %A Mehdi Shahbazian %T Multi-Scale PLS Modeling for Industrial Process Monitoring%T %J International Journal of Computer Applications %V 26 %N 6 %P 26-33 %R 10.5120/3107-4266 %I Foundation of Computer Science (FCS), NY, USA
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.