Use of a Machine Learning based method to detect anomalous Thermoluminescence Glow Curves (TL-GC) in routine Dosimetry Services

IF 1.6 3区物理与天体物理 Q2 NUCLEAR SCIENCE & TECHNOLOGY

Radiation Measurements Pub Date : 2024-09-10 DOI:10.1016/j.radmeas.2024.107293

O. Arquero , J. Berenguer-Antequera , J.F. Benavente

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引用次数: 0

Abstract

This contribution describes the development of a set of numerical methods based on Machine Learning algorithms to generate an automated classification of experimental Thermoluminescence (TL) Glow Curves obtained routinely by Dosimetry Services. This classification will use experimental data historically recorded by Thermoluminescence Dosimeter (TLD) devices and will be based on the search for possible anomalies in the curves. The classifier tool will ease the labelling of experimental data and the detection of anomalies without previous supervision, implying an improvement in the control evaluations in Quality Guarantee Systems often implemented by Dosimetry Services. Furthermore, this study shows that each curve provides information about the status of each dosimeter, and can be used to perform unsupervised classifications of the measurements.

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在常规剂量测定服务中使用基于机器学习的方法检测异常热释光辉光曲线 (TL-GC)

本论文介绍了一套基于机器学习算法的数值方法的开发过程，该方法可对剂量测定服务部门日常获得的实验性热释光（TL）辉光曲线进行自动分类。该分类将使用热释光剂量计（TLD）设备历史记录的实验数据，并基于对曲线中可能存在的异常情况的搜索。分类器工具将简化实验数据的标注和异常检测，而无需事先监督，这意味着剂量测定服务部门通常实施的质量保证体系中的控制评估将得到改进。此外，这项研究还表明，每条曲线都提供了有关每个剂量计状态的信息，可用于对测量结果进行无监督分类。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Radiation Measurements 工程技术-核科学技术

CiteScore

4.10

自引率

20.00%

发文量

116

审稿时长

48 days

期刊介绍： The journal seeks to publish papers that present advances in the following areas: spontaneous and stimulated luminescence (including scintillating materials, thermoluminescence, and optically stimulated luminescence); electron spin resonance of natural and synthetic materials; the physics, design and performance of radiation measurements (including computational modelling such as electronic transport simulations); the novel basic aspects of radiation measurement in medical physics. Studies of energy-transfer phenomena, track physics and microdosimetry are also of interest to the journal. Applications relevant to the journal, particularly where they present novel detection techniques, novel analytical approaches or novel materials, include: personal dosimetry (including dosimetric quantities, active/electronic and passive monitoring techniques for photon, neutron and charged-particle exposures); environmental dosimetry (including methodological advances and predictive models related to radon, but generally excluding local survey results of radon where the main aim is to establish the radiation risk to populations); cosmic and high-energy radiation measurements (including dosimetry, space radiation effects, and single event upsets); dosimetry-based archaeological and Quaternary dating; dosimetry-based approaches to thermochronometry; accident and retrospective dosimetry (including activation detectors), and dosimetry and measurements related to medical applications.