Development of a quantitative evaluation system for static electricity induced luminescence using image proccesing

Static Electricity induced Luminescence (SEL) material ($\mathrm{SrAl}_{2} \mathrm{O}_{4}: \mathrm{Eu}^{2+}$) was recently discovered, which emits luminescence due to external energy from static electric. Static electric that could not be visualized can now be recognized through luminescence and SEL is expected to be a new image-based static electricity sensing technology. In this study, we developed a system to quantitatively evaluate SEL material using image analysis. The experimental results confirm correlation between the applied voltage and the maximum intensity of the SEL.

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Published
2024-11-21
DOI
https://doi.org/10.1109/iciibms62405.2024.10792781
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
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article

Development of a quantitative evaluation system for static electricity induced luminescence using image proccesing

Jin Yien Lee, Kazuya Kikunaga, Osamu Fukuda, Yuki Fujio et al.
Infrared Target Detection Methodologies
article

Development of a quantitative evaluation system for static electricity induced luminescence using image proccesing

Jin Yien Lee, Kazuya Kikunaga, Osamu Fukuda, Yuki Fujio, Taiga Eguchi, Nanami Ishizu
article en

Abstract

Static Electricity induced Luminescence (SEL) material ($\mathrm{SrAl}_{2} \mathrm{O}_{4}: \mathrm{Eu}^{2+}$) was recently discovered, which emits luminescence due to external energy from static electric. Static electric that could not be visualized can now be recognized through luminescence and SEL is expected to be a new image-based static electricity sensing technology. In this study, we developed a system to quantitatively evaluate SEL material using image analysis. The experimental results confirm correlation between the applied voltage and the maximum intensity of the SEL.

Saga University (JP)
Japan Society for the Promotion of Science
Affordable and clean energy
Openalex Percentile: Top 62%
Infrared Target Detection Methodologies
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