% The demos contained in the zip file mpcademo.zip provide examples of
% application of visualization techniques in process applications. These
% demos goes together with the MathWorks News & Notes (Issue: May, 2003)
% article, titled "USING VISUALIZATION TECHNIQUES FOR BATCH CONDITION MONITORING".
% Visit: http://www.mathworks.com/company/newsletter/index.shtml
% This demo contains the following:
% 1. A walk-through example that explains the Multi-way PCA technique for
% analyzing batch processes. Run WALK_THROUGH_DEMO.M in MATLAB. It makes
% use of function COMPUTE_ELLIPSOID.M for generating some volume graphics.
% 2. HTML page: PROCESS_DEMO.HTML This is an html version of the
% 3. Batch Condition Monitoring GUI: this GUI is discussed in the New &
% Notes article. Launch this GUI by running MPCAGUI2C.M.
% The GUI is for illustrative purposes only. By no means is this GUI the
% best or the most efficient procedure (or even a recommended way) for
% performing such analysis. It was put together to support the article.
% IMPORTANT NOTES:
% (a) After downloading and unzipping the files, please ensure that all the
% data files are writable (have full read/write permission). If not, make
% them so.
% (b) The graphics requires OPENGL. To check if you are using OPENGL in
% MATLAB, type: "opengl info" in command window of MATLAB.
% (c) How to use GUI:
% - On left bottom corner of GUI is Analysis Data popup menu. Choose a
% test dataset to emulate the real-life streaming data based condition
% - The panel on the right has several useful controls. Press the "Log
% Data" button to emulate the real-time data-logging. At each logging
% instant, the currently forecasted regions will be drawn at the top
% center of the GUI. The 2-D "shadows" of this 3-D plot are drawn on
% the three sides.
% - For this GUI a 5th order PCA model was used - the primary three are
% shown on the plot, while projections along the rest two are chosen
% from the control panel. To choose projections, drag the blue icon
% around with your mouse, inside the ellipse. Regions outside the
% ellipse are invalid projections. Of the 5 principal components, the
% chosen three to be visualized can be chosen using the 3 popups for
% X, Y and Z axes, also from the control panel.
% - While changing the projected 3-D views by using the data panner, you
% may want to view the locus of all such projections for different
% choices on the panner. This can be done by clicking on the "Show
% Trail" checkbox, located below the main 3-D view axes. Uncheck this
% checkbox and move the icon in the panner to go back to normal view.
% - Control the transparency of intersecting ellipsoids by using the two
% slider bars, located right below the 3-D view axes.
% - Automate the data logging process by pressing the Automate button on
% right-side control panel.
% - Press the Time Evolution button to view an animation of the 3-D
% score predictions at each logging time instant, until the current
% time. This view also contains the time histories of the 12 process
% variables, until the current time. This figure has some control
% options that facilitate interaction, such as transparency control
% and choosing number of ellipsoids to view.
% - View Exterior button: By pressing this button, user can view the
% region of intersection of score ellipsoid with in-control ellipsoid
% - RESETTING Views: This GUI is a prototype only. If at any time, you
% get stuck and can't refresh a view, just choose a new Analysis Data
% from the popup menu (left, bottom). You can re-select the current
% batch also. If you are stuck real bad (with callback errors etc),
% close the GUI and re-launch it by typing "mpcagui2c" in command
% window. Note: OPENGL is required for volume visualization.
% - Please take time to use Camera toolbar - lighting and view control
% options. These tools greatly assist visualization, and also make the
% process fun!
% If you have questions, contact me at firstname.lastname@example.org.
% Have fun!
disp('Please read the help contents of this m-file (>> help readme).')