A Cognitive Filter to Automatically Determine Scintillation Detector Materials and to Control Their Spectroscopic Resolution During Temperature Changes

The shape of the nuclear signal from scintillators contains information about the detection material from which it originated and its current temperature. A digital filter for this type of signals is presented that automatically extracts both of these pieces of information from the shape of the signals and controls the temperature dependency of the resolution by continuous adaption to this shape. Hereby, nuclear signals are a-priori modelled by an all-pole filter. The concept combines a deconvolution approach based on this model with a least-mean-squares iteration. Beneath the iteration, there is a continuous assessment of the signal shape where the mean-squared distance between the assumed shape and measured shape acts as control parameter for the resolution. From the information stored inside the dynamic filter parameters, the material characteristics are retrieved to identify the detector material. An implementation into a multi-channel-analyser is shown and the technique is verified under real-world environmental conditions.