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

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 2006Winery2006

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


This is about...

The Anerobic Wastewater TreatmentThe Monitoring & Control Variables


Application of FDA

Experimentation



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


The Anerobic Wastewater Treatment

The solutionMonitoring 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


This is about...

The Problem

The Monitoring & Control VariablesDiscrimination Statistical Techniques

Application of FDA

Experimentation




Selection Criteria Low response delay High sensibility Low cost of both, sensor itself and its operation-

maintenance requirements.

PreviouslyGas flow rate and H2/CH4 in the gas phaseH2/CO in the gas phase H2 in the gas phase Gas flow rate and CH4 in the gas phaseAlkalinities (total and partial) in the liquid phase pH in the liquid phase and gas flow rate



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?


This is about...

The Problem


Discrimination Statistical TechniquesApplication of FDA

Experimentation




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


altura

peso

.

Hombres

Centroide de hombres

Mujeres

Centroide de Mujeres


Men

Women

Men’s mean

Women’s mean

Height

Weig

ht

-6 -4 -2 0 2 4 6Factor o función discriminante

HombresMujeresPromedio HombresPromedio Mujeres

MenWomenWomen’s meanMen’s mean



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


This is about...

The Problem



Application of FDAExperimentation



Application of FDA

Selection of Variable using FDAFDA 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

FDAMissclassification

Error


This is about...

The Problem



Application of FDA

ExperimentationResults and Conclusions


Experimentation

The pilot plant and its instrumentationA 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).


ExperimentationThe experimental conditions

State Time OLRFeed

flowrateTOC

influent

(d) (kg COD/m3·d) (Qa) (L/h) (mgC/L)

1: (N.O.) 0-4 5 22 3000

2: H.O. 4-9 15 66 3000

3: H.O.+O.O. 9-14 28 66 4500

4: H.O.+O.O. 14-15.5 32 66 6000


This is about...

The Problem



Application of FDA

Experimentation




Selection of Variable using FDAClassification analysis was made using 1 variable, all the combination of 2 variables and so on.

50

60

70

80

90

100

QH

2

H2

Qga

s P

%C

H4

QC

H4

pH o

ut

OLR

TO

C in

f

pH e

ff

EtO

H in

f

TO

C e

ff

EtO

H e

ff

TIC

eff

Pro

p in

f

DIC

eff

DO

C e

ff

Ace

t in

f

TIC

inf

Ace

t ef

f

Qa Tr

But

inf

Pro

p ef

f

Tin Qr

Variables

Good c

lass

ific

atio

n (%

) .



Selection of Variable using FDA137 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

Qa

58.9Tin

58.655Tr

63.655.658.9Qr

10099.1100100P

10098.59498.899.1%CH4

100100100100100100H2

10096.299.492.3100100100pHeff

88.890.892.382.810010010092.9DOCeff

89.688.889.68210010010092.390.5DICeff

88.287.686.48710010010010098.593.8TOC eff

93.594.194.485.510010010092.391.485.597.9

10095.699.493.51001001009594.193.810096.4

88.892.692.680.21001001009292.683.796.286.494.7

10099.110010010099.1100100100100100100100100

10098.810098.510099.1100100100100100100100100100

10098.298.597.910010010010010099.798.899.710099.1100100

10098.210098.210099.410099.710098.810099.710098.895100100

99.794.798.888.510010010091.789.692.910093.893.299.710010010099.7

88.886.188.281.410098.510094.485.286.1978795.687.910099.196.299.792.3

92.390.591.784.610099.110092.689.687.397.989.393.889.610098.596.29590.583.7

65.157.160.157.110010010092.379.68287.985.593.581.410010098.898.288.282.286.1

94.190.294.786.710010010092.986.791.498.891.793.892.610010010010088.287.990.586.1

7981.785.271.310010010092.986.485.896.289.994.189.610010099.198.291.181.186.47187.3

65.157.160.157.110010010092.379.68287.985.593.581.410010098.898.288.282.286.157.186.171

100100100100100100100100100100100100100100100100100100100100100100100100100



Other criteriaConstant temperature, influent pH and recirculation flow rate.Specific substance determinations in the liquid phase are rare in industrial applicationQgas and P highly are correlated High cost of the on line equipment for TIC/TOC on line measurementVariables in the liquid phase are supposed to present higher response time than the gas phase variables



The selected variables were QH2, H2, Qg, QCH4 ,

CH4

1

2

3

4

5

6

7

8

9 10

Process State

1

2

3

4

5

6

7

8

9 10

1

2

3

4

5

6

7

8

9 10

1

2

3

4

5

6

7

8

9 10

Process State



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)


For more information...

María Castellano Méndez

[email protected]

Dep. of Statistics and O.R. University of Santiago de Compostela, Spain

Gonzalo Ruiz Filippi

[email protected]

School of Biochemical Engineering. Catholic University of Valparaiso, Chile

Documents

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