The FEE Server Control Engine of the ALICE-TRD - Westfälische ...

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ADC difference (a.u.) 120 100 80 60 40 20 6 Temperature Monitoring of the Front End Readout Electronics 0 0 20 40 60 80 100 120 time (min) Figure 6.6: MCM temperature sensor data with fitted simple exponential functions (solid lines). The data are the same already shown in figure 6.3. 3. The factors 50, 10 and 20 in formula 6.3 are weighting coefficients. It turned out that the differences in the fit parameters between cooled and uncooled MCMs are bigger in region 1 than in the other two regions. Therefore this part is given a larger weight. Two examples of the final cooling overview showing the score values of all MCMs in a layer are given in figure 6.8 and 6.9. The two plots show the score value of the same layer obtained in different measurements. The measurement for plot 6.8 was done about half an hour after an electronics stress test. Therefore the layer was not completely cooled down at the beginning of the measurement. The other measurement was done after the layer had been switched off for more than one day. As a result the average score value in plot 6.8 is higher than in plot 6.9. However, the bad cooled MCMs are clearly identifiable in both plots due to their higher score value compared to the other MCMs. Furthermore one can see the effect of the MCM temperature readout unreliability. All MCMs with no score value in the plots had a non-working temperature sensor during the measurement (except the MCMs in columns 60 – 75 in plot 6.8). Some MCMs have a score value only in the first and other only in the second plot. The analysis program All the analysis functions described in the last section have been compiled to one ROOT library named libTempAlys.so. The library contains the class LayerTemp which provides the commands necessary to analyze the recorded temperature data. When ROOT is running, first the library has to be loaded with the command gSystem −>Load("libTempAlys.so"). Afterwards one has to create a instance of the contained class via the command LayerTemp * layer= new LayerTemp. Now ROOT provides the following commands for the data analysis: • layer−>loadRootFile("filename"): Add a data file. All files have to belong to the same layer. 84
magnitude magnitude magnitude 0 -10 -20 -30 -40 -50 -60 6 Temperature Monitoring of the Front End Readout Electronics -70 -0.25 -0.2 -0.15 -0.1 -0.05 0 slope 0 -5 -10 -15 -20 -25 -30 -35 -40 -0.25 -0.2 -0.15 -0.1 -0.05 0 slope 30 25 20 15 10 5 0 -0.3 -0.25 -0.2 -0.15 -0.1 -0.05 0 slope magnitude magnitude magnitude 0 -10 -20 -30 -40 -50 -60 0 10 20 30 40 50 60 70 80 limit 0 -10 -20 -30 -40 -50 0 20 40 60 80 100 120 140 160 limit 30 25 20 15 10 5 0 0 10 20 30 40 50 60 70 80 90 limit Figure 6.7: Scatter plots of the magnitude as a function of slope (left column) and magnitude as a function of limit (right column) from equation 6.2. Blue points are the fit parameters from cooled MCMs and red points are the fit parameters from uncooled MCMs. The two uppermost plots show the fit parameters from fitting the data in region 1, the two plots in the middle show the fit parameters for region 2 and the remaining two plots show the fit parameters from region 3. The positions of the three regions were shown in figure 6.3. 85
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5.2.4 Sensor Monitoring . . . . . .
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1 Introduction The standard model o
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2 Theoretical background first gene
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Temperature (MeV) 225 200 175 150 1
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2 Theoretical background Cold dense
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3 LHC and the ALICE experiment The
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4.1.2 Readout Chamber Design 108.16
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Average pulse height (mV) 4 The ALI
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