Machine learning assisted optical diagnostics on a cylindrical surface dielectric barrier discharge
D Stefas,
K Giotis,
L Invernizzi
et al.
Abstract:The present study explores combining machine learning (ML) algorithms with standard optical diagnostics (such as time–integrated emission spectroscopy and imaging) to accurately predict operating conditions and assess the emission uniformity of a cylindrical surface Dielectric Barrier Discharge (SDBD). It is demonstrated that these optical diagnostics can provide the input data for ML which identifies peculiarities associated with the discharge emission pattern at different high voltage waveforms (AC and pulse… Show more
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