PoLogCem
4. The “Pollution's Modelling” panel
The contents
4. The “Pollution's Modelling” panel
4.1. How to manage the measurements during the modelling process?
4.2. How to build nonlinear regression models for the pollution generated by a
cement plant?
4.3. How to generate graphical representations?
4.4. How to generate and view the pollution map in a dynamical way?
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PoLogCem
4.1. How to manage the measurements
during the modelling process?
The functionalities provided by the modelling module were already reported at some
conferences like PSAM107 - ESREL’04 in Berlin, ENBIS2 in Copenhagen, and IWES3
in Romania. The approach was covered also in a short paper published by Scientific
World Computing4. However, there are some improvements in the final stage,
including piecewise modelling and the dynamic pollution map visualization. The user
will appreciate, also, a better graphical interface (location of the buttons, visualizing style
etc.).
According to the Fig. 1, for the model’s output measurements tab, in the left
panel are presented the measurements prepared by the plant's logistic module, and in
the right panel are presented the output values that are issued in the mathematical
models determination. The “>” buttons will permit to obtain the selected line from the
1
H. Madsen, P. Thyregod, Fl. Popentiu Vladicescu, G. Albeanu & L. Serbanescu,
A Decision Support System for Pollution Control in Cement Plants, Proceedings of
PSAM 07 - ESREL'04, June 14-18, 2004, Berlin. In: C. Spitzer, U. Schmocker si V.N.
Dang (editors), Probabilistic Safety Assessment and Management, Vol. 3, pp. 17841789, Springer; ISBN: 1-85233-827-X
2
Henrik Madsen, Poul Thyregod, Florin Popentiu & Grigore Albeanu, Computer
Aided Modelling and Pollution Control in Cement Plants, The 4th ENBIS Conference,
Copenhagen, 20-22 September 2004,
http://www.enbis.org/copenhagenconference/abstracts.html (index by number: 84)
3
Fl. Popentiu, G. Albeanu & L. Serbanescu, A software system for controlling the
pollution dynamics in the cements plants, Proc. of the 5th International Word Energy
System Conference, May, 17-19, 2004, Oradea, Vol. III, pp. 437-442, ISSN: 1198-0729.
4
Henrik Madsen, Poul Thyregod, Florin Popentiu & Grigore Albeanu, Computer
Aided Modelling and Pollution Control in Cement Plants, The 4th ENBIS Conference,
Copenhagen, 20-22 September 2004,
http://www.enbis.org/copenhagenconference/abstracts.html (index by number: 84)
4-2
right side, while pushing the “>>>” button, the user will obtain data in the whole right
table. When the EMPTY TABLE button is pressed then the corresponding table will
be emptied. Similar actions are necessary when the Output Measurements tab is
selected.
Existing measurements provided by the Logistic module
To transfer only the selected line
To transfer the whole list
Fig. 1. Defining the output models
The setting procedure dealing with output-input dependences for the models that will
be created it is shown in the Fig. 2. For each selected output (made up by module's
point name and the parameter's name) will be created a list (the table) with the
depending parameters. The user will start to insert and fill the rows in the table with
x1, x2, x3, ... symbols, in the symbol field of the table.
In the lower part, the user will select the corresponding parameters for each row
in the table. The measurement point type (input / output) is compulsory to be selected.
The delta [h] (in the fifth column) field is referring to the measurement's displacement
(diphase), in this case the measurement lapse of time is bigger than the greatest
displacement (diphase). The Date Time 1 and Date Time 2 (in the Fig. 2, see also the
Fig. 4) were inserted in order to define the interval of time that will be taken into
consideration (if it is nothing inserted then it will assume the already existent interval
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of time). The Tolerance [h] field (the last column in the Fig. 2) will provide the
maximal admitted time difference to be considered when two parameters assumed
values simultaneously. The format for date / time can be easily set up using the Control
Panel module from the Microsoft Windows Environment, as shown in the Fig. 3.
Fig. 2. Defining the output-input dependencies for models that will be considered for
pollution modelling and other studies
Fig. 3. Setting up the format for date / time (by Control Panel)
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Table with values
corresponding to the
selected variable.
Press this button in order to search for the values corresponding to
the variable (already selected).
Fig. 4. Finding X-values corresponding to the X - variables
Also the management of the input-output date is provided as shown in the Fig. 4. For
each variable Xi it is obtained the table of values by pushing the FIND X VALUES
button. The Scroll bar can be used to see more data in the table (Fig. 5). To delete the
corresponding table of values it is enough to push the EMPTY TABLE button.
The table with
variables and time
intervals for the
values
Fig. 5. The Environmental map example
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PoLogCem
4.2. How to build the nonlinear regression
models for the pollution generated by a
cement plant?
The images presented in the next figures illustrate the steps to follow in designing the
data models. Firstly, the user will select the output measurement and then push the
DISPLAY TABLE button and the results will be displayed as correspondence table
for the selected output measurement with all the values of the input measurements for
the corresponding output. Both classical and piecewise modeling is possible. In the
Fig. 6, is shown a classical modeling. Considering interval data, the piecewise
modeling is possible as shown in the Fig. 7.
Press here to see the table of data
The selection of the
output model
Here, there is the table containing the
data related to dependent (Y) and
independent (X) variables.
Fig. 6. The automatic loading of values for the output dependent variable
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The table of intervals to be considered for
the selected parameter
The data can be exported to XLD / Dbase files
Fig. 7. Piecewise modelling
Functions defined
by user. After
solving the model,
the coefficients
are shown in the
third column.
Press the button to
solve the model.
Fig. 8. Defining the structure of the regression model
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In order to determine the mathematical models the following information is valuable:
the output measurement must be selected and then in the left-down table will be filled
the linear/nonlinear functions in a manner enabling us to obtain a model with the
following expression:
y = A0+ A1*F1(x1, ..., xm) + A2*F2(x1, ..., xm) + AnFn(x1, x2, …, xm),
where m is the number of independent variables, and y is the dependent variable. The
functions F1, F2,…, Fm must be defined by the user in the editing window (the right
^
down corner in the Fig. 8). Let us denote by Yk si Yk the measured respective the
computed output variable, and by Y , the mean value of the variable Y given by the
values Yk , k = 1, 2, … . Let Sy be the deviance to the mean of the measured data, and
S ^ be the deviance from the mean of the data obtained after the solving of the
y
M
M
^
regression model. Therefore, S y   (Yk  Y ) 2 and S ^   (Yk  Y ) 2 . To compare the
y
k 1
k 1
measured model against de regression model, the software uses the following indicator
S^
(adequacy level): R 2  Y .
SY
The adequacy
index
Press button for
more Knowledge
to be added in the
Database Rules.
It is shown the measured versus modeled
data in the case of the dependent variable.
Fig. 9. Updating the Knowledge Database
Note: The software PoLogCem uses the notation R instead of R2 (Fig. 8 and Fig. 9).
After the model was created (the structure was established and the coefficients were
found) it will be added (using the button APPEND TO DATABASE RULES) to the
existing general set of rules (Fig. 9). The name (label) of the new rule is automatically
generated. The rules are needed to the optimization module.
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PoLogCem
4.3. How to generate graphical representations?
The modeling module also provides graphical representations. Firstly, the
output parameter will be selected. All corresponding graphics will be automatically
updated. In the upper panel the user will see the model's output and the measured
output and, in the lower panel, the difference between them (using the sum of
differences). The image provided in the Fig. 10 illustrates the mentioned results.
If you want to obtain a WMF / BMP file
Press here to select the parameter
Y measured
(red) versus the
model (green)
It is shown the difference between
the measured data and the model
data.
Fig. 10. Graphical representations: Y modelled versus Y measured
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PoLogCem
4.4. How to generate and view the pollution map
in a dynamical way?
Fig. 11 presents the initial state during the pollution map generation. The user can
change the time to see a new map. The user will select the parameter which spreading
in area to be calculated and viewed. The left-down rectangle will be filled at the
moment of time when the view is wanted. Then the QUERY button will be pushed to
determinate the values of the selected parameter for all measurement points at the
mentioned moment of time. Finally the user will push the MAP PROCESSING
button and the map will be built and displayed. The obtained map can be copied in the
clipboard as BMP file. The map pollution is shown in the Fig. 12 both in static and
dynamic manner. Also the pollution level can be obtaining when moving the mouse
over the map (Fig. 13).
Firstly, select the polluting
parameter
Select the position (East, North, South, West – V, PLANT)
Here, will be
generated the map
after pressing the
MAP PROCESSING
button.
Press this
button to fill
the left table
with data.
This button will be used for the dynamical visualization
Fig. 11. The map generation - initial state
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Here is defined the time interval for the
map generation.
Select the timing and press the MAP
EVOLUTION button for the movie.
Fig. 12. The Pollution Map
The pollution level is viewed here,
when moving the mouse over the map.
Fig. 13. The Pollution Level
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