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Optimization of the DC Power Supply Measurement System for Heavy Ion Accelerators

Published: 20 June 2024 Publication History

Abstract

Optimizing the existing data readback system of heavy ion accelerator power supplies, a new data measurement system was designed on an independently developed digital power controller. This was aimed at replacing the existing power readback systems on certain heavy ion accelerator power supplies to reduce hardware costs. Modifications were made to the FPGA parameters controlling the ADC within the controller, and a data interaction supervisory control and data acquisition (SCADA) system was developed on the computer side. The system converts the analog signals from the power supply into digital signals, which are then transmitted to the supervisory computer. The data is then filtered using MATLAB to obtain the final results. Comparison with the existing power measurement systems showed that the optimized data measurement system could replace the existing power measurement systems in scenarios where short-term measurement of a large amount of data is required.

References

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Cui Yuan. Research on real-time digital control regulator of heavy ion accelerator power supply. University of Chinese Academy of Sciences (Institute of Modern Physics, Chinese Academy of Sciences),2018
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Huang Yuzhen; Youxin Chen; Yan Huaihai. Research and Design of Digital Power Regulator based on FPGA [J]. Nuclear Electronics and Detection Technology,2010(10)
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Zhang Huajian; Wu Fengjun; Huang Yuzhen. Heavy ion accelerator digital power readback system. Atomic Energy Science and Technology,2018(06)
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Wang Rongkun; Youxin Chen; Yan Huaihai; Huang Yuzhen; Gao Daqing; Zhou Zhongzu; Zhao Jiang; Wu Fengjun; Yan Hongbin; Zhang Huajian; Feng Xiuming. Digital Power Regulation System of Ion Cancer Accelerator [P]. China Patent :2012-05-23
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Gao Yajun, Ed. Digital Signal Processing based on FPGA [M]. Publishing House of Electronics Industry.2012
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He Zhiyang. Design and Implementation of Digital Controller Based on domestic FPGA Accelerator Power [D]. University of Electronic Science and Technology of China,2022
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CMLDS '24: Proceedings of the International Conference on Computing, Machine Learning and Data Science
April 2024
381 pages
ISBN:9798400716393
DOI:10.1145/3661725
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 June 2024

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  1. Software and its engineering • Software creation and management • Designing software • Software design engineering

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  • National key research and development plan

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CMLDS 2024

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