Nuclear counting filter based on a Centered Skellam Test and a double Exponential Smoothing
Résumé
Online nuclear counting represents a challenge due to the stochastic nature of radioactivity. The count data have to be filtered in order to provide a precise and accurate estimation of the count rate, this with a response time compatible with the application in view. An innovative filter is presented in this paper addressing this issue.
It is a nonlinear filter based on a Centered Skellam Test (CST) giving a local maximum likelihood estimation of the signal based on a Poisson distribution assumption. This nonlinear approach allows to smooth the counting signal while maintaining a fast response when brutal change activity occur. The filter has been improved by the implementation of a Brown's double Exponential Smoothing (BES). The filter has been validated and compared to other state of the art smoothing filters. The CST-BES filter shows a significant improvement compared to all tested smoothing filters.
Mots clés
Filter
Signal Processing
Nuclear
Measurement
nuclear counting filter
Poisson distribution
radioactivity
radioactivity measurement
local maximum likelihood estimation
nonlinear filter
stochastic nature
Brown double exponential smoothing
centered Skellam test
maximum likelihood estimation
Index Terms-Nuclear
Origine | Fichiers produits par l'(les) auteur(s) |
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