Interpreting neural networks trained to predict plasma temperature from optical emission spectra

Képeš, Erik; Saeidfirozeh, Homa; Laitl, Vojtěch; Vrábel, Jakub; Kubelík, Petr; Pořízka, Pavel; Ferus, Martin; Kaiser, Jozef

doi:10.1039/d3ja00363a

J. Anal. At. Spectrom.

2024

DOI: 10.1039/d3ja00363a

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Interpreting neural networks trained to predict plasma temperature from optical emission spectra

Erik Képeš,

Homa Saeidfirozeh,

Vojtěch Laitl

et al.

Abstract: We explore the application of artificial neural networks (ANNs) for predicting plasma temperatures in Laser-Induced Breakdown Spectroscopy (LIBS) analysis. Estimating plasma temperature from emission spectra is often challenging due to...

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Cited by 3 publications

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Machine learning in laser-induced breakdown spectroscopy: A review

Hao,

Liu,

Lian

et al. 2024

Front. Phys.

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Machine learning in laser-induced breakdown spectroscopy: A review

Hao,

Liu,

Lian

et al. 2024

Front. Phys.

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Laser-induced breakdown spectroscopy in space applications: Review and prospects

Saeidfirozeh,

Kubelík,

Laitl

et al. 2024

TrAC Trends in Analytical Chemistry

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Correlation of Plasma Temperature in Laser-Induced Breakdown Spectroscopy with the Hydrophobic Properties of Silicone Rubber Insulators

Kokkinaki,

Siozos,

Mavrikakis

et al. 2024

Chemosensors

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In this study, we have investigated the relationship between the plasma temperature in remote laser-induced breakdown spectroscopy (LIBS) experiments and the hydrophobic properties of silicone rubber insulators (SIRs). Contact angle and LIBS measurements were conducted on both artificially-aged (accelerated aging) and field-aged SIRs. This study reveals a clear connection between plasma temperature and the properties of aged SIRs on artificially-aged SIR specimens. Specifically, the plasma temperature exhibits a consistent increase with the duration of the accelerated aging test. The hydrophobicity of the artificially-aged SIRs was assessed by performing contact angle measurements, revealing a decrease in the hydrophobicity with increased aging test duration. Furthermore, we extended our investigation to the study of nine field-aged SIRs that had been in use on 150 kV overhead transmission lines for 0 to 21 years. We find that the laser absorption and hardness of the material do not relate to the plasma temperature. In summary, we observe a direct connection of plasma temperature to both contact-angle measurements and operation time of the in-service insulators. These results strongly suggest the potential use of LIBS for remotely evaluating the hydrophobicity and aging degree of silicone rubber insulators, thus assessing their real-time on-site operational quality.

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Interpreting neural networks trained to predict plasma temperature from optical emission spectra

Abstract: We explore the application of artificial neural networks (ANNs) for predicting plasma temperatures in Laser-Induced Breakdown Spectroscopy (LIBS) analysis. Estimating plasma temperature from emission spectra is often challenging due to...

Cited by 3 publications

References 93 publications

Machine learning in laser-induced breakdown spectroscopy: A review

Machine learning in laser-induced breakdown spectroscopy: A review

Laser-induced breakdown spectroscopy in space applications: Review and prospects

Correlation of Plasma Temperature in Laser-Induced Breakdown Spectroscopy with the Hydrophobic Properties of Silicone Rubber Insulators

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