Strong Radiation Field Online Detection and Monitoring System with Camera.
CMOS
camera
monitoring
monolithic active-pixel sensors
online radiation detection
strong radiation field
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
16 Mar 2022
16 Mar 2022
Historique:
received:
21
02
2022
revised:
10
03
2022
accepted:
14
03
2022
entrez:
26
3
2022
pubmed:
27
3
2022
medline:
1
4
2022
Statut:
epublish
Résumé
Herein, we report the γ-ray ionizing radiation response of a commercial monolithic active-pixel sensor (MAPS) camera under strong-dose-rate irradiation with an online detection and monitoring system for strong radiation conditions. We present the first results of the distribution of three types of MAPS camera and establish a linear relationship between the average response signal and radiation dose rate in the strong-dose-rate range. There is an obvious response signal in the video frames when the camera module parameters are set to automatic, but the linear response is very poor. However, the fixed image parameters are not good at adapting to the changes of the environment and affect the quality of the video frames. A dual module online radiation detection and monitoring probe was made to carry out effective video monitoring and radiation detection at the same time. The measurement results show that the dose rate detection error is less than 5% with a dose rate in the range of 60 to 425 Gy/h, and the visible light image does not have obvious distortion, deformation, or color shift due to the interference of the radiation response event and radiation damage. Hence, the system test results show that it can be used for online detection and monitoring in a strong radiation environment.
Identifiants
pubmed: 35336450
pii: s22062279
doi: 10.3390/s22062279
pmc: PMC8955199
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : General nuclear safety technology
ID : xxx080202
Organisme : National Natural Science Foundation of China
ID : 11905102
Organisme : Natural Science Foundation of Hunan Province
ID : 2020JJ5499
Organisme : Education Department of Hunan Province
ID : 18B268
Références
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pubmed: 25985207
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pubmed: 27136556
Opt Express. 2021 Oct 25;29(22):34913-34925
pubmed: 34808940