Casestudie Breakdown prediction Contell PILOT - Transumo

As all these software products fail to offer a satisfying solution, Matlab is used in the
following to implement the suggested methods. In fact, also Matlab has some
problems to import the original datasets, but these problems can easily be solved by
changing some delimiters in the CSV file. 75 Moreover, Matlab is capable of importing
date and time correctly and is able to process very large datasets.
In the following, the general ideas of the made implementation will be introduced.
The technical realization and annotations to occurred problems, due to Matlab’s
limited programming possibilities, can be found in the appendix.
Caused by the storage behavior of XiltriX 76 the stored values contain different time
intervals. An example of this behavior is pictured in Figure 6-1. But the suggested
analyzing methods from section 5.10 assume constant time ranges. Hence, the first
step of data analysis is an interpolation of the stored datasets.
The basic idea is, to create new datasets of measurement values that contain regular
time intervals. Door openings are stored to the beginning of the minute, in which they
occur. A combination of the original and the interpolated datasets can be used to
calculate the desired values, as described in the following, without making
adaptations to the described methods. Certainly, in case of an implementation to
XiltriX, its storage behavior should be adapted, so that interpolation is not necessary
any more.
After this interpolation, the desired statistical measures can be calculated. Therefore,
the original and the interpolated datasets are divided into single days and these days
again into daytime and nighttime. As described in section 5.10.1, daytime limits can
be obtained by analyzing the door openings. Based on these made classes, the
promising measures maximum, minimum, mean, standard deviation and the number
of door openings can be calculated on the aimed basis of daytime, nighttime and
whole day.
To obtain correct results, the calculation of minimum and maximum values has to be
based on the original data to avoid smoothing. By contrast, mean as well as standard
deviation has to be based on the interpolated data to achieve a correct weighting in
time. The determination of door openings can be based on both datasets, because
the number of door openings remains unchanged after interpolation. The also aimed
goal, to plot a temperature distribution, can be implemented easily by just counting
75 See appendix for details
76 See section 3.2.1 for details
87