Evaluation of a one-dimensional position-sensitive quartz optical fiber sensor based on the time-of-flight method for high radiation dose rate applications

Terasaka, Yuta; Watanabe, K.; Uritani, Akira

doi:10.1016/j.nima.2021.165151

Cited by 4 publications

(1 citation statement)

References 5 publications

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“…Meanwhile, Song et al [6] optimized the back-end amplifier and digital signal processing (DSP) based on the TOF method to enhance the sensitivity and accuracy of the PSF detector. Terasaka et al [7] investigated the use of quartz optical fiber instead of PSF for radiation detection. They found that the quartz optical fiber has significantly higher position resolution, which…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-based reconstruction of single and double radiation source distribution using plastic scintillation optical fiber

Dai,

Geng,

Tang

2023

J. Inst.

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In this study, we propose a novel method for reconstructing the radiation distribution of a one-dimensional radioactive source using Machine Learning (ML) algorithms and plastic scintillation optical fiber. The wavelength spectrum unfolding technique is used to estimate the source position accurately. We compare the accuracy and time efficiency of three different algorithms, namely, Generalized reduced gradient (GRG), Maximum likelihood expectation maximization (MLEM), and ML, in the single-source and dual-source cases. Our results demonstrate that MLEM algorithm has a shorter reconstruction time with comparable accuracy of position and intensity compared to GRG algorithm for single-source case. For dual-source case, ML algorithm provides real-time estimation of position and intensity with acceptable errors, while GRG algorithm has a larger error in intensity estimation and longer computation time. Our proposed ML algorithms offer useful guidance for practical applications in radiation source location.

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Section: Introductionmentioning

confidence: 99%