Difference between revisions of "Assignment 4"
Kevin Dunn (talk | contribs) m |
Kevin Dunn (talk | contribs) m |
||
| Line 2: | Line 2: | ||
<rst-options: 'toc' = False/> | <rst-options: 'toc' = False/> | ||
Please provide **short** answers (no more than 5 pages, including all your plots) to the questions below. Here is some `background reading for this assignment < http://literature.connectmv.com/item/124>`. | Please provide **short** answers (no more than 5 pages, including all your plots) to the questions below. Here is some `background reading for this assignment <http://literature.connectmv.com/item/124>`_. | ||
The aim is to build a soft-sensor model for Kappa number, which is measured at the outlet of the Kamyr digester. This creates problems with feedback control to keep :math:`y` on target. Long time delays exist between variables that affect :math:`y`, and those columns have been time-shifted already to align the data. | The aim is to build a soft-sensor model for Kappa number, which is measured at the outlet of the Kamyr digester. This creates problems with feedback control to keep :math:`y` on target. Long time delays exist between variables that affect :math:`y`, and those columns have been time-shifted already to align the data. | ||
| Line 8: | Line 8: | ||
We already examined in class the important variables that affect :math:`y` = Kappa number. Now your task is to build as good a soft-sensor model as possible using `the extended data set <http://latent.connectmv.com/images/0/06/Kamyr-full.csv>`_. | We already examined in class the important variables that affect :math:`y` = Kappa number. Now your task is to build as good a soft-sensor model as possible using `the extended data set <http://latent.connectmv.com/images/0/06/Kamyr-full.csv>`_. | ||
Using the data from a bleach kraft mill in Alberta, build a soft sensor model using observations of the first | Using the data from a bleach kraft mill in Alberta, build a soft sensor model using observations of the first 2400 hours (40 days of data). Then test your model's prediction ability on data from hours 2400 to 3400, and hours 3400 to 4400. | ||
For each of these prediction periods, show time-series plots of | For each of these prediction periods, show time-series plots of | ||
Revision as of 17:38, 30 October 2011
<rst> <rst-options: 'toc' = False/>
Please provide **short** answers (no more than 5 pages, including all your plots) to the questions below. Here is some `background reading for this assignment <http://literature.connectmv.com/item/124>`_.
The aim is to build a soft-sensor model for Kappa number, which is measured at the outlet of the Kamyr digester. This creates problems with feedback control to keep :math:`y` on target. Long time delays exist between variables that affect :math:`y`, and those columns have been time-shifted already to align the data.
We already examined in class the important variables that affect :math:`y` = Kappa number. Now your task is to build as good a soft-sensor model as possible using `the extended data set <http://latent.connectmv.com/images/0/06/Kamyr-full.csv>`_.
Using the data from a bleach kraft mill in Alberta, build a soft sensor model using observations of the first 2400 hours (40 days of data). Then test your model's prediction ability on data from hours 2400 to 3400, and hours 3400 to 4400.
For each of these prediction periods, show time-series plots of
- SPE,
- :math:`T^2`,
- and plot observed *and* predicted on a time-series plot (not the usual scatter plot)
- Also calculate RMSEP for the prediction periods.
How do you rate the soft-sensor's performance? </rst>