4.7 Article

Artificial olfaction based on tafel curve for quantitative detection of acetone ethanol gas mixture

Journal

SENSORS AND ACTUATORS B-CHEMICAL
Volume 377, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA

Keywords

Finite element method; Machine learning; Mixed potential gas sensor; Tafel curve; Artificial olfactory

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This study developed an artificial olfaction system using a single mixed potential type gas sensor. By analyzing the Tafel curve, the system can accurately determine the concentration of acetone and ethanol in a vapor mixture. To save time, a finite element model was used to simulate different concentrations of vapor mixtures. Classification algorithms were trained using the Tafel curve data, achieving 99% accuracy in detecting sensor saturation. Regression algorithms were then used to identify acetone and ethanol concentrations, with the most effective being eXtreme Gradient Boosting (XGB) and Gradient Boosting Decision Tree (GBDT). The results showed mean absolute percentage errors of 11.3% for acetone and 23% for ethanol. Overall, using Tafel curves to detect VOC gases is feasible and effective.
This work established an artificial olfaction based on a single mixed potential type gas sensor. By identifying the Tafel curve, artificial olfaction can determine the concentration of each component in the acetone and ethanol vapor mixture. To save a long testing circle, a finite element model was built to efficiently output the Tafel curves of the sensor for different concentrations of vapor mixtures. Based on the Tafel curve data obtained from the simulation, different classification algorithms were trained to determine the operating state of the sensor. Among them, eXtreme Gradient Boosting (XGB) had a 99% accuracy in determining whether the sensor is saturated or not. Then three different regression algorithms (XGB, Gradient Boosting Decision Tree (GBDT), and Random Forest (RF)) were trained to identify acetone and ethanol vapor concentrations. The results showed that XGB and GBDT were the most effective in identifying acetone and ethanol vapor. The mean absolute percentage errors for the identified acetone and ethanol in the gas mixture were 11.3% and 23%, respectively. The above results indicated that it was feasible and effective to use Tafel curves to detect VOC gases.

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