Dynamic Derivative Convolution Algorithm For Prompt Gamma Neutron Activation Spectra

A technique is presented to algorithmically evaluate prompt gamma neutron activation spectra, which were produced through excitation of specific material samples. The excitation is done with a neutron generator that provides a switchable, artificial form of neutron radiation. To evaluate the spectra, a extension to prior peak based analysis methods is proposed that dynamically incorporates the detector resolution over the full energy range. Based on this technique a series of measured response spectra are analyzed and the material composition or the samples is identified. Materials of cement and coal mining industry are considered. Limits of the detection limits and confidence thresholds are presented.