Tunable diode laser absorption spectroscopy (TDLAS) technology holds significant potential for greenhouse gas detection, due to its advantages of non-contact, real-time measurements. However, the technical bottleneck of cross-interference in gas absorption spectra has significantly constrained the development and application of this technique in simultaneous measurement of multi-component gases.
Researchers develop neural network algorithm to enhance gas detection technology
