Abstract
In recent years, digital processing algorithms have been widely applied in spectrum processing applications. Besides, FPGA technology, thanks to its undeniable advantages in flexibility, high integration, and cost-effectiveness, is seriously considered as a practical platform for the realization of embedded digital signal processing (DSP) systems.
This work conducts a study on the practical implementation of Digital Multi-channel Analyzer (DMCA) based on reconfigurable hardware (FPGA). We proposed a modular reconfigurable DMCA design that is ready to be integrated into portable radiation detecting equipment and is still capable to handle high-speed signal sampling as well as could be extended to further functions such as remote sensing and classifying. This module could be integrated into the real-time radiation monitoring system. The algorithms of pulse shaping filter, detecting peaks and spectrum histogram processing are optimized and implemented entirely using available FPGA logic resources.
The design is experimentally verified in a system using Lanthanum Bromide Scintillation Radiation LaBr3(Ce) detector. The results are compared with commercial products (DSPEC of ORTEC), where isotopes 137Cs and 60Co gamma-ray spectra show that its performance partially is superior to the DSPEC in terms of full width at half maximum (FWHM), received and lost count rate, integral nonlinearity. This prototype system is highly promising for the multi-DMCA system in considering performance, cost, and form factors. Regarding resource utilization and performance, the whole design utilizes only 5% LEs, 24% memory resources of 10M50SAE144I7G FPGA from Intel and the DMCA core is capable to handle up to 97 MSPS sampling rates.
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Notes
- 1.
We did not compare resource utilization of our work with [5] since that work used CPLD device that is not based on Logic Element primitives.
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Trinh, QK., Trinh, VN., Le, TB., Dinh, TH., Cao, VH. (2021). An Embedded Digital Multi-channel Analyzer for Radiation Detection Based on FPGA. In: Vo, NS., Hoang, VP., Vien, QT. (eds) Industrial Networks and Intelligent Systems. INISCOM 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 379. Springer, Cham. https://doi.org/10.1007/978-3-030-77424-0_18
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