Research Article

Multi-Scale PLS Modeling for Industrial Process Monitoring

by  Mohammad Sadegh Emami Roodbali, Mehdi Shahbazian
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 26 - Issue 6
Published: July 2011
Authors: Mohammad Sadegh Emami Roodbali, Mehdi Shahbazian
10.5120/3107-4266
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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
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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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Process monitoring fault wavelet PLS multi-scale

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