1. Selection of variables using FDA for the state identification of an Anaerobic UASB-UAF hybrid Pilot Plant, fed with winery effluents. M. Castellano 1, G. Ruiz 2, W. González 1, E. Roca 3 and J.M. Lema 3 1 Dep. of Statistics and O.R. University of Santiago de Compostela, Spain 2 School of Biochemical Engineering. Catholic University of Valparaiso, Chile 3 Dep. 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. Winery2006, Viña del Mar This is about... The Anaerobic Wastewater Treatment The Monitoring & Control Variables Discrimination Statistical Techniques Application of FDA Experimentation Results and Conclusions

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

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

5. Winery2006, Viña del Mar 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) First requirement: Selecting process variables

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

7. Winery2006, Viña del Mar 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 H 2 /CH 4 in the gas phase H 2 /CO in the gas phase H 2 in the gas phase Gas flow rate and CH 4 in the gas phase Alkalinities (total and partial) in the liquid phase pH in the liquid phase and gas flow rate

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

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

10. Winery2006, Viña del Mar 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 Maximize variance between groups Together

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

12. Winery2006, Viña del Mar 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 Only complex to explain, not to USE

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

14. Winery2006, Viña del Mar 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. All combination of variables FDA Missclassification Error

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

16. Winery2006, Viña del Mar 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 CH 4 ) (QH 2 ) and organic loading rate (OLR).

17. Winery2006, Viña del Mar Experimentation The experimental conditions Stable conditions at an OLR of 5 kg COD/m 3 ·d. Three consecutive increases of the OLR until SS. The duration of each state was around 5 days, (HRT was in the range of 0.6 to 1.5 d.)

18. Winery2006, Viña del Mar Experimentation The experimental conditions StateTimeOLR Feed flowrate TOC influent (d)(kg COD/m 3 ·d)(Qa) (L/h)(mgC/L) 1: (N.O.) 0-45223000 2: H.O. 4-915663000 3: H.O.+O.O. 9-1428664500 4: H.O.+O.O. 14-15.532666000

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

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

21. Winery2006, Viña del Mar 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

22. Winery2006, Viña del Mar 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

23. Winery2006, Viña del Mar Results and Conclusions The selected variables were QH 2, H 2, Qg, QCH 4, CH 4

24. Winery2006, Viña del Mar 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 (H 2 )

25. Winery2006, Viña del Mar 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