Study of n-γ discrimination in low energy range (above 40 keVee) by charge comparison method with a BC501A liquid scintillation detector

Chen, Yonghao; Chen, Ximeng; Zhang, Xiaodong; Jiarong, Lei; Liu, An; Shao, Jianxiong; Peng, Zheng; Wang, Xinhua; Chuanxin, Zhu; He, Tao; Yang, Jiankun

doi:10.1088/1674-1137/38/3/036001

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…By resolving this issue, neutron detection technologies will be more widely used. Currently, charge comparison [4], rise time [5], zero-crossing [6], and frequency gradient analysis [7] methods are frequently employed in pulse shape discrimination (PSD), and particularly the charge comparison method is used as the default PSD method in many studies since it's highly dependable. Despite the charge comparison method has a good discriminating performance on single pulses, numerous complex circumstances such as piled-up pulses and overflowed pulses will change the pulse structure [8].…”

Section: Introductionmentioning

confidence: 99%

Neutron-gamma events discrimination under complex circumstances using ResNet

Song

Yang

et al. 2023

J. Inst.

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On scintillator detectors, neutron and gamma rays could generate signals. These signals are generated internally and cannot be shielded, and there are various complex circumstances during data collection, such as piled-up pulse at high count rates and overflowed pulse caused by detector range limits. It is challenging to screen these complex circumstances using conventional methods like charge comparison. Conventional methods have low accuracy and lack self adaptability, to address these problem, a neural network based on residual connection structure (ResNet) was proposed. On the basis of the collected real signal, the pulse waveforms under complex circumstances were simulated. After integrating these waveforms into a dataset, they were trained and validated by ResNet and compared with two neural network algorithms MLP and CNN. The false predictions number of ResNet is 60% and 73% lower than that of CNN and MLP. The macro average F1 score of ResNet was 0.9956, which was significantly higher than 0.9885 of CNN and 0.9855 of MLP. And in the ROC and AUC, ResNet is still the best performing method, furthermore the improvement of ResNet to CNN is higher than that of CNN to MLP. These results indicated that Proposed ResNet is more suitable for neutron-gamma events discrimination in complex situations.

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Section: Introductionmentioning

confidence: 99%

Neutron-gamma events discrimination under complex circumstances using ResNet

Song

Yang

et al. 2023

J. Inst.

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“…It has been found that all neutron fields coexist with associated γ-ray backgrounds, arising as a result of reactions of the neutrons with materials in the environment and as direct byproducts of the primary reaction producing the neutron field. Therefore discriminating neutrons against a γ-ray background plays an essential role in detecting neutrons effectively [1]. Over the past few decades, various methods using analog circuit technology have been developed for n-γ discrimination, such as the Rise Time Method [2][3][4] and the Charge Comparison Method [5,6].…”

Section: Introductionmentioning

confidence: 99%

Improvement of algorithms for digital real-time n- γ discrimination

王宋¹,

许鹏²,

鲁昌兵³

et al. 2016

Chinese Phys. C

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Three algorithms (the Charge Comparison Method, n-γ Model Analysis and the Centroid Algorithm) have been revised to improve their accuracy and broaden the scope of applications to real-time digital n-γ discrimination. To evaluate the feasibility of the revised algorithms, a comparison between the improved and original versions of each is presented. To select an optimal real-time discrimination algorithm from these six algorithms (improved and original), the figure-of-merit (FOM), Peak-Threshold Ratio (PTR), Error Probability (EP) and Simulation Time (ST) for each were calculated to obtain a quantitatively comprehensive assessment of their performance. The results demonstrate that the improved algorithms have a higher accuracy, with an average improvement of 10% in FOM, 95% in PTR and 25% in EP, but all the STs are increased. Finally, the Adjustable Centroid Algorithm (ACA) is selected as the optimal algorithm for real-time digital n-γ discrimination.

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“…It is highly desirable to detect both fast and thermal neutrons, in order to perform accurate neutron dosimetry in an energy distributed field. Using a liquid scintillator with current state-of-the-art pulse shape discrimination techniques (PSD), neutron interactions in the detector can be discriminated from gamma interactions down to around 40 keVee [1]. This equates to a neutron energy of approximately 450 keV, although this is dependent on a number of factors including detector dimensions and type of scintillant [2].…”

Section: Introductionmentioning

confidence: 99%

Neutron assay in mixed radiation fields with a⁶Li-loaded plastic scintillator

2015

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A novel technique for assay of thermal and fast neutrons in a 6 Li-loaded plastic scintillator is presented. Existing capture-gated thermal neutron detection techniques were evaluated with the 6 Li-loaded plastic scintillator studied in this work. Using simulations and experimental work, shortcomings in its performance were highlighted. As a result, it was proposed that by separating the combined fast and thermal neutron events from gamma events, using established pulse shape discrimination techniques, the thermal neutron events could then be assayed. Experiments were conducted at the National Physical Laboratory, Teddington, performing neutron assays with seven different neutron fields using the proposed technique. For each field, thermal and fast neutron content was estimated and were shown to corroborate with the seven synthesised fields.

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Study of n-γ discrimination in low energy range (above 40 keVee) by charge comparison method with a BC501A liquid scintillation detector

Cited by 10 publications

References 14 publications

Neutron-gamma events discrimination under complex circumstances using ResNet

Neutron-gamma events discrimination under complex circumstances using ResNet

Improvement of algorithms for digital real-time n- γ discrimination

Neutron assay in mixed radiation fields with a⁶Li-loaded plastic scintillator

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Study of n-γ discrimination in low energy range (above 40 keVee) by charge comparison method with a BC501A liquid scintillation detector

Cited by 10 publications

References 14 publications

Neutron-gamma events discrimination under complex circumstances using ResNet

Neutron-gamma events discrimination under complex circumstances using ResNet

Improvement of algorithms for digital real-time n- γ discrimination

Neutron assay in mixed radiation fields with a6Li-loaded plastic scintillator

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Neutron assay in mixed radiation fields with a⁶Li-loaded plastic scintillator