29th Symposium on Fusion Technology (SOFT 2016)

P4.088 Automatic pattern recognition on electrical signals applied to Neutron-Gamma discrimination

8 Sep 2016, 14:20

1h 40m

Foyer 2A (2nd floor), 3A (3rd floor) (Prague Congress Centre)

Board: 88

Poster D. Diagnostics, Data Acquisition and Remote Participation P4 Poster session

Speaker

Fabio Pollastrone (FSN (Nuclear Fusion and Fission and Related Technologies Department))

Description

The electrical pattern recognition can be useful in several applications, generally it is used to detect particular events or anomalies in the signal under analysis or to identify precursors, especially in electrophysiology. Each application requires customized algorithms and appropriate signal processing capabilities. In this paper we present an application of pattern recognition to real-time discrimination of neutrons and gamma rays detected by liquid scintillators; the discrimination is possible because the two particles incident the detector produce pulses having different shape. A general-purpose algorithm is proposed that can be efficiently implemented in a programmable logic gate array; this allows the development of efficient and low-cost systems for the electrical pattern recognition which, with minor changes, can be applied to different diagnostic fields.The discrimination of particles is performed starting from a reference patterns set. This reference set can be simple and with a limited number of patterns; however the hardware implementation may result complex, due to the high bandwidth of the signals under analysis. The proposed pattern recognition algorithm is based on the cross-correlation operator and on the definition of a norm related to the difference between the reference pattern and the shape of the actual signal. The automatic pattern recognition algorithm, the digital hardware implementation, its software, as well as the simulations done in case of general purpose patterns and are described in the paper. Moreover, in order to verify the performances in the case of scintillator signals, the algorithm has been applied on data acquired by a scintillator system irradiated by a neutron-γ source at the Frascati Tokamak Upgrade laboratories. The results confirm the suitability of the method and its future usability.