Detectors Calibration

Jul 1, 2016 - Detectors plugged into the DAQ. ➔ Need to understand the errors. ○ How ? ➔ Find a reproducible method. ➔ Analyse data with Python ...
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Internship Presentation

Detectors Calibration Under the supervision of Nicolas Delerue

BONAMY Geoffrey

01/07/2016

Contents I. Introduction II.Theory III. Experiment equipment IV. Acquisition module characterization V.Detectors calibration 01/07/2016

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INTRODUCTION ●

Coherent SmithPurcell Radiation



Pyrodetectors

Fig. Nicolas Delerue

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THEORY Coherent Smith-Purcell Radiation Coherence :

Bunches Size : Picosecond bunch

300μm

Wavelength :

Fig. Nicolas Delerue

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EXPERIMENT EQUIPMENT

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Pyrodetectors Sensitive part Surface Charge :

Current :

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Acquisition Module 1 2 3 4

Channels input Connections Trigger input Supply input

The DAQ have Two thread : ●



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Read from the ADC and save in files Communication with the user with an interface.

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Acquisition Module Communication Each channel is referenced by is number ( 0 to 7 ) Value for the Amplitude and Offset goes from 0 to 255

Characteristics Give an answer on 4.096V. Coded in 8 bits gives 256 values

Uncertainty on each sample in Volts : 4.096/256 = 16mV

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DAQ Characterization ●



Why ? ➔

Detectors plugged into the DAQ



Need to understand the errors

How ? ➔

Find a reproducible method



Analyse data with Python

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DAQ Characterization Approach ●

Reproducible Assembly ➔

Pulse generator. ➔ ➔ ➔



Very precise different signals shapes Tree to split the signal

Code in python ➔

Licence free

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DAQ Characterization Approach

Observations ●

30Hz

50Hz



70Hz 01/07/2016

Dependency : Amplitude/ frequency Difference between the 8 Channels response

100Hz Bonamy Geoffrey

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DAQ Characterization Approach

Solution Fit : Offset + A * sin(ω*x + φ ) ●

Python code using curve_fit* function ●

Analyse Amplitude, offset, sampling rate.



Uncertainty on the value

*Return the best parameters using non linear least squares method.

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DAQ Characterization Approach

Uncertainties 16mV uncertainty included in the fit function. ● Plot on 1800 samples Uncertainty order : 0,1 mV for 30Hz and 50Hz. 1mV for 70Hz and 100Hz. ●

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Amplitude Link with the frequency

Oscilloscope signal 01/07/2016

Acquisition with the DAQ Bonamy Geoffrey

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Amplitude



Link with the frequency



Difference regarding : ● ●

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Channels Days

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Offset





No significant link with the frequency during one day. Difference regarding : ● ●

Channels Days within the uncertainty

Easily manageable.

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Sampling rate

No Difference regarding : ● ●

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Channels Days

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DAQ Characterization Conclusion

Amplitude

Offset

Sampling rate

Variation with channels

Yes

Yes

No

Variation regarding the day

Yes

Yes

No

Variation with frequency

Yes

Not significant

X

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Detectors Calibration Assembly Pyrodetectors

Light bulb

Translation stage

f=10cm Lens

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Parabolic Mirror

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Detectors Calibration Photo-diode Intensity and translation characterization

Conversion between Motor steps and mm 100 000 steps = 7.79mm ± 0.61

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Detectors Calibration Misalignment

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Transversal

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Detectors Calibration Misalignment

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Longitudinal

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Conclusion DAQ characterization Assembly characterisation Detectors calibration with light Studies with IR and FIR

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