TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
Proposed set up
Automatic assessment of biological treatability of textile wastewaters
using a neural network
Lettinga Associates Foundation
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
About this work
• Extra work based on finished WP’s:– WP05.02.5
(Development of on-line wastewater characterisation techniques)
– WP05.04.05(Respirometric on-line tests)
implementation of the on-line respirometric technique: “Protocol WW Design i.t.o. treatability”
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
Automation
• Automatic decision stream is biologically treatable or not
• Using data from respirometric (BODst) and infrared measurements (COD)
• COD/BOD indicates treatability
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
Schematic
Respirometer
IR meter
Decision fortreatment
option
COD
Respirogram
CODBOD
Extradata
BOD(st)
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
0
10
20
30
40
-10 10 30 50t (min)
R (
mg/lh
)Respirogram analysis - Human
• Let’s see:1) height2) end length3) area4) basic rate OK?normal shape?
1
23
4
• Easy!
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
0
10
20
30
40
-10 10 30 50t (min)
R (
mg/lh
)
3
Respirogram analysis - Computer
• Let’s see:1) height2) end length3) area4) basic rate OK?normal shape?
1
2 2 2
4
• Quite difficult!
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
In practice: more possible shapes
• Dilemma:
The end of the respirogram
0
10
20
30
40
50
-10 10 30 50 70 90t (min)
R
?
?
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
0
5
10
15
20
-10 10 30 50 70 90(min)
R
In practice: more shapes
• Dilemma:
Basic rate can change during measurement
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
Neural network (NNW)
• Basic difference with “normal” model:– It can work with similarities instead of just
“identical” and “different”
• Based on data training sets, NNW can learn and give the most probable outcome
• In this case, the NNW should be trained for each different wastewater type
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
Work involved
• Building of neural network (NNW)
• Recording of respirograms to test computer model with similar yet different effluents
• Training the NNW to recognise respirogram characteristics and calculate BOD(st)
• Measuring “infrared COD” for same samples
TOWEF0 - Paris - October 2003 Lettinga Associates Foundation
Respirograms
• Respirograms have been recorded with I09 samples from five different acid dyeing wastewaters (dyebaths and rinsing steps)
• In case more are needed to test the model, old respirograms may be used– Neural network needs the shapes to be similar
for successful training
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