To analyse drill samples in a mine, a scanner that uses a gamma ray detector can be used. The scanner can analyse the drill sample to quickly see the elements present in the sample without destroying it. To improve the performance of the scanner, the electric signal from the detector needs to be less noisy, and different pulse shaping methods, filters and smoothers can be used on the sampled data to achieve an improved performance. In this master thesis, the electric noise model of the electronics around the detector was modeled, and analysed. Different pulse shaping method, filters and smoothers was also tested to see which method gave the best performance in FWHM sense. The Full Width at Half Maximum (FWHM) is the energy resolution of a detector, and is defined as the full width of a photopeak at the half maximum. The noise model of the schematic for the preamplifier was made by hand with support from MATLAB. The resulting noise model was compared between MATLAB and LTspice, and the conclusion is that the JFET is the main contributor of the significant noise, contributing to 98 % of the total noise at 10 GHz. The adopted filters and pulse shaping method are, matched filter, custom filter, CR-RC shaping, mean filter, median filter and clustering. The results from the tests indicated that custom filter with a FWHM of 1.96 keV and CR-RC with a FWHM of 1.67 keV shaping were more accurate than the matched filter with the FWHM of 5.1 keV. But the results also showed that it is important to take into account the waveform variance, due to inherent properties in the detector, with this consideration the FWHM of CR-RC shaper was improved from 2.29 keV to 1.67 keV. The clustering method was the most promising method but due to time constraints this method was never fully tested and no FWHM value was achieved.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-66637 |
Date | January 2017 |
Creators | Ödmark, Fredrik |
Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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