Fault Detection of Drinking Water Treatment Process Using PCA and Hotelling's T2 Chart
This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling-s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling-s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment Works downloaded from an Integrated Program Management (IPM) dashboard system. The analysis of the results show that Multivariate Statistical Process Control (MSPC) techniques such as PCA, and control charts such as Hotelling-s T2, can be effectively applied for the early fault detection of continuous multivariable processes such as Drinking Water Treatment. The software package SIMCA-P was used to develop the MSPC models and Hotelling-s T2 Chart from the collected data.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072862Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
 De Vaux R, Ungar L, Vinson J (2007, June 5), Statistical Approaches to Fault Analysis in Multivariate Process Control
[Online]. Available: http://citeseer.ist.psu.edu
 Klancar G, Fault Detection and Isolation by means of Principal Component Analysis, Faculty of Electrical Engineering, University of Ljubliana, Ljubliana, Slovenia.
 Lennox B, Montague G, Marjanovic O (2007, June 19) Detection of faults in Batch Processes: Application to an industrial fermentation and a steel making process
[Online]. Available: http://www.forumira. com/pdf/4conf3.pdf
 McGregor J, Kourti T, (1994), Process analysis, monitoring and diagnosis, using multivariate projection methods, Chemometrics and Intelligent Laboratory Systems 28 (1995) 3-21.
 Praus P, Water quality assessment using SVD-based principal component analysis of hydrological data, Department of Analytical Chemistry and Material Testing, VSB-Technical University Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic
 Ruiz M, Colomer J and Mel'endez J, Multiway Principal Component Analysis and Case Base-Reasoning approach to situation assessment in a Waste Water Treatment Plant ,Control Engineering and Intelligent Systems Group -eXiT, Department of Electronics, Computer Science and Automatic Control University of Girona, Campus Montilivi CP 17071 Building PIV, Girona - Spain
 Wise B. (2007 June 30). Adapting Multivariate Analysis for Monitoring and Modeling of Dynamic Systems, University of Washington. Partial Least Squares
[Online]. Available: http://www.statsoft.com/textbook/stpls.html, on June 30,2007