Login / Signup

Tailored Algorithm for Sensitivity Enhancement of Gas Concentration Sensors Based on Tunable Laser Absorption Spectroscopy.

Everardo Vargas-RodriguezAna Dinora Guzman-ChavezRoberto Baeza-Serrato
Published in: Sensors (Basel, Switzerland) (2018)
In this work, a novel tailored algorithm to enhance the overall sensitivity of gas concentration sensors based on the Direct Absorption Tunable Laser Absorption Spectroscopy (DA-ATLAS) method is presented. By using this algorithm, the sensor sensitivity can be custom-designed to be quasi constant over a much larger dynamic range compared with that obtained by typical methods based on a single statistics feature of the sensor signal output (peak amplitude, area under the curve, mean or RMS). Additionally, it is shown that with our algorithm, an optimal function can be tailored to get a quasi linear relationship between the concentration and some specific statistics features over a wider dynamic range. In order to test the viability of our algorithm, a basic C 2 H 2 sensor based on DA-ATLAS was implemented, and its experimental measurements support the simulated results provided by our algorithm.
Keyphrases
  • machine learning
  • deep learning
  • neural network
  • high resolution
  • single molecule
  • solid state
  • low cost
  • quantum dots
  • functional connectivity