Deep learning-based fast time-resolved flame emission spectroscopy in high-pressure combustion environment. (arXiv:2208.12544v1 [cs.LG])

A novel deep learning strategy is developed for fast and accurate gas
property measurements using flame emission spectroscopy (FES). Particularly,
the short-gated fast FES is essential to resolve fast-evolving combustion
behaviors. However, as the exposure time for capturing the flame emission
spectrum gets shorter, the signal-to-noise ratio (SNR) decreases, and
characteristic spectral features indicating the gas properties become
relatively weaker. Then, the property estimation based on the short-gated
spectrum is difficult and inaccurate. Denoising convolutional neural networks
(CNN) can enhance …

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