Principal Component Analysis applied to neutron dosimetry based on PADC detectors and FNTDs

Solid State Nuclear Track Detectors (SSNTD) have been used as passive dosimeters for many decades. Fast neutron detection is performed by detecting recoil protons generated in a hydrogenous material (neutron converter). The dose estimated multiplying the track-spots density present on detector surface calibration coefficient obtained from reference irradiations. Therefore, one needs to automatically and reliably discriminate between induced recoil-protons spurious signal engendered either imperfections or other ionising particles interactions. objective of this work demonstrate apply method, based multivariate statistical tool named Principal Component Analysis (PCA), aiming at identifying filtering out track detectors. advantage approach that it can be applied any type SSNTD, provided apt definition initial physical variables describing each track-spot. To show that, we method poly-allyl diglycol carbonate (PADC) detectors, filter imperfections, fluorescence nuclear detectors (FNTDs), remove radiation field components. After filtering, assessments were compared with values exposures, showing satisfactory agreement. In case FNTDs, procedure proved effective regardless crystal colouration, which known affect signal-rejection techniques intensity. technique also offers self-adjusting parameters currently analysed set, long unirradiated are included dataset.