M. Castellano 1 , G. Ruiz 2 , W. González 1 , E. Roca 3 and J.M. Lema 3

1. Selection of variables using FDA for the state identification of an Anaerobic UASB-UAF hybrid Pilot Plant, fed with winery effluents. M. Castellano1, G. Ruiz 2, W. González1, E. Roca3 and J.M. Lema3 1Dep. of Statistics and O.R. University of Santiago de Compostela, Spain 2School of Biochemical Engineering. Catholic University of Valparaiso, Chile 3Dep. of Chemical Engineering. School of Engineering. University of Santiago de Compostela, Spain IV International Specialized Conference on Sustainable Viniculture: Winery Wastes and Ecology Impact Management Viña del Mar – Chile, November 2006 Winery2006

2. This is about... • The Anaerobic Wastewater Treatment • The Monitoring & Control Variables • Discrimination Statistical Techniques • Application of FDA • Experimentation • Results and Conclusions Winery2006, Viña del Mar

3. This is about... • The Anerobic Wastewater Treatment The Monitoring & Control Variables Discrimination Statistical Techniques Application of FDA Experimentation Results and Conclusions Winery2006, Viña del Mar

4. Changes in the Operation Conditions The Anerobic Wastewater Treatment The treatment characteristics Requires low energy& Generates low sludges. The problem Variations over Influent properties and composition Monitoring Diagnosis and Control System (MD&C) FORStable Operation Conditions Winery2006, Viña del Mar

5. First requirement: Selectingprocess variables The Anerobic Wastewater Treatment The solution Monitoring Diagnosis and Control System (MD&C) : • early and automatic detection of perturbations (overload, presence of toxic, inhibitory compounds, suddenly changes in pH) Winery2006, Viña del Mar

6. This is about... The Problem • The Monitoring & Control Variables Discrimination Statistical Techniques Application of FDA Experimentation Results and Conclusions Winery2006, Viña del Mar

7. The Monitoring & Control Variables Selection Criteria • Low response delay • High sensibility • Low cost of both, sensor itself and its operation-maintenance requirements. • Previously • Gas flow rate and H2/CH4 in the gas phase • H2/CO in the gas phase • H2 in the gas phase • Gas flow rate and CH4 in the gas phase • Alkalinities (total and partial) in the liquid phase • pH in the liquid phase and gas flow rate Winery2006, Viña del Mar

8. FDA Classify between different S.S. Diagnose the process performance. Group of variables All combination of variables Usefull for diagnosis? The Monitoring & Control Variables The statistical analysis Functional Discriminant Analysis (FDA) Classification Select the minimum number of variables for process state identification purpose. Winery2006, Viña del Mar

9. This is about... The Problem The Monitoring & Control Variables • Discrimination Statistical Techniques Application of FDA Experimentation Results and Conclusions Winery2006, Viña del Mar

10. Together Discrimination Statistical Techniques Functional Discriminant Analysis (FDA) • Simple Statistical Classification Tool • Linear Transformation of process variables • Requires: A priori knowledge about groups • Objectives: • Minimize the missclassification error • Minimize variance into each group • Maximizevariance between groups Winery2006, Viña del Mar

11. Men Women Women’s mean Men’s mean Discrimination Statistical Techniques Men Weight Men’s mean Women Women’s mean Height Winery2006, Viña del Mar

12. Only complex to explain, not to USE Discrimination Statistical Techniques Other techniques of classification Consider more sophisticated functions lead to more sophisticated classification techniques. Some of the more popular and useful • Quadratic discrimination • Non parametric density estimation functions • Neural networks Winery2006, Viña del Mar

13. This is about... The Problem The Monitoring & Control Variables Discrimination Statistical Techniques • Application of FDA Experimentation Results and Conclusions Winery2006, Viña del Mar

14. FDA All combination of variables Missclassification Error Application of FDA Selection of Variable using FDA FDA assigns data to different groups. The FDA classification is tested using all the possible combinations of the variables in order to select the best ones, so the most useful variables for MD&C. Winery2006, Viña del Mar

15. This is about... The Problem The Monitoring & Control Variables Discrimination Statistical Techniques Application of FDA • Experimentation Results and Conclusions Winery2006, Viña del Mar

16. Experimentation The pilot plant and its instrumentation A UASB-UAF pilot plant fed with diluted wine. 26 variables were used to follow the process. Measurement devices • feed and recycling flow meters • pH meter • inflow and reactor Pt100 • gas flow meter • infrared gas analyser (CH4 and CO) • gas hydrogen analyser • TOC/TIC combustion analyser Other parameters were calculated: methane and hydrogen flow rate (Q CH4) (QH2) and organic loading rate (OLR). Winery2006, Viña del Mar

17. Experimentation The experimental conditions Winery2006, Viña del Mar

18. This is about... The Problem The Monitoring & Control Variables Discrimination Statistical Techniques Application of FDA Experimentation • Results and Conclusions Winery2006, Viña del Mar

19. Results and Conclusions Selection of Variable using FDA Classification analysis was made using 1 variable, all the combination of 2 variables and so on. Winery2006, Viña del Mar

20. Results and Conclusions Selection of Variable using FDA 137 of the combination of 2 variables achieve a 100% of goodness classification. The solution is not unique, so another criteria should be used to select the variables for monitoring Winery2006, Viña del Mar

21. Results and Conclusions Other criteria • Constant temperature, influent pH and recirculation flow rate. • Specific substance determinations in the liquid phase are rare in industrial application • Qgas and P highly are correlated • High cost of the on line equipment for TIC/TOC on line measurement • Variables in the liquid phase are supposed to present higher response time than the gas phase variables Winery2006, Viña del Mar

22. Results and Conclusions The selected variables were QH2, H2, Qg, QCH4 , CH4 Winery2006, Viña del Mar

23. Results and Conclusions • Not subjective technique to select the variables that should be used for an MD&C system was developed. • Not only one group of variables that must be selected, but many combinations can achieve same performance. • Economical and technical criteria have been considered. • Gas phase variables obtain good results, even if only one variable is selected (H2) Winery2006, Viña del Mar

24. For more information... María Castellano Méndez mcaste@usc.es Dep. of Statistics and O.R. University of Santiago de Compostela, Spain Gonzalo Ruiz Filippi gonzalo.ruiz@ucv.cl School of Biochemical Engineering. Catholic University of Valparaiso, Chile Winery2006, Viña del Mar