A cognitive filter to stabilize peak positions and widths of a scintillation detector and to determine its material

A digital filter is presented that adapts automatically to the shape of a nuclear signal to stabilise against temperature induced peak shifting. The filter is called cognitive as it extracts the information about the exponential decays and determines the scintillation material intrinsically. The latter is done with a pole deconvolution approach.Based on the knowledge of the decays, the peak position in the pulse-height spectrum is stabilised due to the relationship between exponential decay and temperature. To achieve this, the peak positions are experimentally acquired within a climate chamber measurement and later fed into a learning artificial neural network. This network has additionally access to the decay times, the temperature and the speed and direction of the temperature. The filter is called every two minutes, automatically collecting a series of 500 suited signals and performing an update of the stabilisation. In tests, the temperature induced peak shifting was corrected within a 0.2% boundary. An additional output result of the filter is the material type of the scintillator. For the most materials, temperature curves are known and the assessment of the exponential decay is shown to lead straightforwardly to a determination of the material. Also the hot plugging of two materials is possible, yielding a recovery time of approximately four minutes for the system to adapt to the new material.