The PolySense team has just published a new article on Optics Express Journal reporting on an end-to-end methane gas detection algorithm based on transformer and multi-layer perceptron (MLP) for tunable diode laser absorption spectroscopy (TDLAS). It consists of a Transformer-based U-shaped Neural Network (TUNN) filtering algorithm and a concentration prediction network (CPN) based on MLP. This algorithm employs an end-to-end architectural design to extract information from noisy transmission spectra of methane and derive the CH4 concentrations from denoised spectra, without intermediate steps. For concentration prediction, the determination coefficient (R2) reached 99.7%. Even at low concentrations, R2 remained notably high, reaching up to 89%. The proposed algorithm results in a more efficient, convenient, and accurate spectral data processing for TDLAS-based gas sensors.
The following link provides access to the article: