Information and Communication Technology Seminar, Vol. 1 No. 1, August 2005
ISSN 1858-1633 2005 ICTS 26
Main TS - Stage Temperature 1__Main TS 70
75 80
85 90
95 100
105 110
1 245
489 733
977 1221 1465 1709 1953 2197 2441 2685 2929
waktu menit te
m p
[C ]
Main TS - Stage Temperature 14__Main TS 64.5
64.6 64.7
64.8 64.9
65 65.1
65.2 1
248 495
742 989 1236 1483 1730 1977 2224 2471 2718 2965
waktu menit te
m p
[ C
]
B - Comp Mole Frac Methanol 0.02
0.04 0.06
0.08 0.1
0.12 0.14
0.16 0.18
1 248
495 742
989 1236 1483 1730 1977 2224 2471 2718 2965
waktu menit me
th an
o l
D - Comp Mole Frac Methanol 0.979
0.981 0.983
0.985 0.987
0.989 0.991
0.993 0.995
0.997 1
252 503
754 1005 1256 1507 1758 2009 2260 2511 2762 3013
waktu menit m
e th
a n
o l
3. RESULTS 3.1 Soft sensor
Methodology to build soft sensor is begin from design APRBS Amplitude Pseudo Random Binary
Signal[5], generate data set for training, train ANN soft sensor and validate it.
Soft sensor built by ANN with Multi layer Percepton MLP, Neural Network AutoRegresive,
eXternal input structure NNARX [2], forward model has 6 history lengths and 13 hidden nodes, which
trained by using Levenberg Marquard learning algorithm for 200 times computer iteration is the best
ANN structure to produce good RMSE.
Input layer Hidden layer
Output Layer
Fig. 3. ANN Architecture based temperature correlation
Xd k Xd k-1
Xd k-5 L k
L k-1 L k-5
Qr k Qr k-1
Qr k-5 Xb k
Xb k-1 Xb k-5
1
tgh tgh
tgh
tgh
tgh tgh
tgh
1
Lin
Lin
Xd k
Xb k
tgh = tangen hiperbolik Lin = linier
Input layer Hidden layer
Output Layer
Fig. 4. ANN architecture based flow rate correlation
Figure 3 is ANN soft sensor structure based temperature correlation and Figure 4 is ANN soft
sensor structure based flow rate correlation
3.2 Using Temperature Correlation
The strongest relation with XD is 14
th
tray temperature, and the strongest relation with Xb is 1
st
tray temperature. So, temperature sensor must be place only on tray 1
st
tray and 14
th
tray.
CT
CT TT
TT TT
Temperature Measurement R
L D
V Xd
Xb B
F, Xr
Qr Qc
PC
LC LC
Fig. 5. Temperature Sensor of Distillation Column
In fact, temperature sensor usually available on each tray but only temperature sensor on tray 1
st
tray and 14
th
tray that will be used by soft sensor.Figure 5.
Figure 6 is data set temperature and product composition of distillation column, which use for
training data.
Fig. 6. Data set for training ANN soft sensor based temperature correlation
500 1000
1500 2000
2500 3000
3500 0.98
0.985 0.99
0.995 1
Xd output 2 Solid : process output
Dash : model output
Fig. 7. Xd process and ANN based temperature output comparation
Ann Soft Sensor to Predict Quality of Product Based on Temperature or Flow Rate Correlation – Totok R. Biyanto
ISSN 1858-1633 2005 ICTS 27
500 1000
1500 2000
2500 3000
3500 -0.02
0.02 0.04
0.06 0.08
0.1 0.12
0.14 0.16
0.18 Xb output 1
Solid : process output Dash : model output
Fig. 8. Xb process and ANN output based temperature
comparation ANN Soft sensor based temperature correlation
has Root Mean Square Error RMSE which equal with 5,9908 x 10
-5
for the mole fraction of distillate and RMSE is equal with 1,2686 x 10
-4
for the mole fraction of bottom. Figure 7 and 8
3.3. Using Flow Rate Correlation
Fig. 9. LV control strategy
Fig. 10. Data set for training ANN soft sensor based flow rate correlation
Reflux flow rate L and steam flow rate at reboiler Qr usually use for controlling mole fraction distillate
Xd and mole fraction bottom product Xb at binary distillation column, especially for LV control strategy
is the best pairing composition control to keep composition product Figure 9. It is mean that flow
rate of reflux L has strongest correlation with Xd and steam flow rate at reboiler Qr has strongest
correlation with Xb.
Respect to this correlation, ANN soft sensor built by training ANN soft sensor using L-Xd and Qr-Xb
data sets. Figure 10
Fig. 11. Xd process and ANN based flow rate output comparation
.
Fig. 12. Xb process and ANN based flow rate output comparation
Soft sensor which using correlation between reflux flow rate L and mole fraction of distillate Xd
has Root Mean Square Error RMSE which equal with 6,6589x10-5 and soft sensor which using
correlation with steam flow rate at reboiler Qr has RMSE is equal with 1,98100x10-4 for the mole
fraction of bottom Xb Figure 11 12.
Soft sensor has fast respon performance, better of reliability because of temperature and flow rate
measurement instrumentation have better reliability compare to analyzer reliability, cheaper, low
operational and maintenance cost.
Information and Communication Technology Seminar, Vol. 1 No. 1, August 2005
ISSN 1858-1633 2005 ICTS 28
4. CONCLUSION
