Empirical Modal Decomposition Combined with Deep Learning for Photoacoustic Spectroscopy Detection of Mixture Gas Concentrations

In photoacoustic spectroscopy based multicomponent gas analysis, the overlap of the absorption spectra among different gases can affect the measurement accuracy of gas concentrations. We report a multicomponent gas analysis method based on empirical modal decomposition (EMD), convolutional neural ne...

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Veröffentlicht in:	Analytical chemistry (Washington) 2024-11, Vol.96 (46), p.18528-18536
Hauptverfasser:	Gong, Zhenfeng, Fan, Yeming, Guan, Yuchen, Wu, Guojie, Mei, Liang
Format:	Artikel
Sprache:	eng
Schlagworte:	absorption Absorption spectra Acetylene Ammonia analytical chemistry Artificial neural networks data collection Decomposition Deep learning Distributed feedback lasers Gas analysis Gases Long short-term memory Machine learning Mixtures Neural networks Photoacoustic spectroscopy Random noise Spectroscopic analysis Spectroscopy Spectrum analysis
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