An embedded system for gamma and neutron discrimination in mixed radiation environments is proposed, validated with an off-the-shelf detector consisting of a Cs2LiYCl6:Ce (CLYC) crystal coupled to a silicon photomultiplier (SiPM) cell array. This solution employs a machine learning classification model based on a multilayer perceptron (MLP) running on a commercial Field-Programmable Gate Array (FPGA), providing online single-event identification with 98.2% overall accuracy at rates higher than 200 kilocounts per second. Thermal neutrons and fast neutrons up to 5 MeV can be detected and discriminated from gamma events, even under pile-up scenarios with a dead-time lower than 2.5 μs. The system exhibits excellent size, weight, and power consumption (SWaP) characteristics, packed in a volume smaller than 0.6 liters and weighing less than 0.5 kilograms, while ensuring continuous operation with only 1.5 Watt. These features render our proposal suitable for embedded applications where low SWaP is critical and radiation levels manifest large count rate variability, such as space exploration, portable dosimeters, radiation surveillance on uncrewed aerial vehicles (UAV), and soil moisture monitoring.

Gamma/neutron online discrimination based on machine learning with CLYC detectors

Iván René Morales
Primo
Writing – Original Draft Preparation
;
Romina Soledad Molina
Secondo
Data Curation
;
Giovanni Ramponi
Penultimo
Formal Analysis
;
Sergio Carrato
Ultimo
Supervision
2024-01-01

Abstract

An embedded system for gamma and neutron discrimination in mixed radiation environments is proposed, validated with an off-the-shelf detector consisting of a Cs2LiYCl6:Ce (CLYC) crystal coupled to a silicon photomultiplier (SiPM) cell array. This solution employs a machine learning classification model based on a multilayer perceptron (MLP) running on a commercial Field-Programmable Gate Array (FPGA), providing online single-event identification with 98.2% overall accuracy at rates higher than 200 kilocounts per second. Thermal neutrons and fast neutrons up to 5 MeV can be detected and discriminated from gamma events, even under pile-up scenarios with a dead-time lower than 2.5 μs. The system exhibits excellent size, weight, and power consumption (SWaP) characteristics, packed in a volume smaller than 0.6 liters and weighing less than 0.5 kilograms, while ensuring continuous operation with only 1.5 Watt. These features render our proposal suitable for embedded applications where low SWaP is critical and radiation levels manifest large count rate variability, such as space exploration, portable dosimeters, radiation surveillance on uncrewed aerial vehicles (UAV), and soil moisture monitoring.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3099219
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