Neural Network Based Aliasing Spectral Decoupling Algorithm for Precise Mid-Infrared Multicomponent Gases Sensing

Owing to the overlapping and cross-interference of absorption lines in multicomponent gases, the simultaneous measurement of such gases via laser absorption spectroscopy frequently necessitates the use of supplementary pressure sensors to distinguish the spectral lines. Alternatively, it requires multiple lasers combined with time-division multiplexing to independently scan the absorption peaks of each gas, thereby preventing interference from other gases. This inevitably escalates both the cost of the system and the complexity of the gas pathway. In response to these challenges, a mid-infrared sensor employing a neural network-based decoupling algorithm for aliasing spectral is developed, enabling the simultaneous detection of methane(CH