RESUMO
New process developments linked to Power to X (energy storage or energy conversion to another form of energy) require tools to perform process monitoring. The main gases involved in these types of processes are H2, CO, CH4, and CO2. Because of the non-selectivity of the sensors, a multi-sensor matrix has been built in this work based on commercial sensors having very different transduction principles, and, therefore, providing richer information. To treat the data provided by the sensor array and extract gas mixture composition (nature and concentration), linear (Multi Linear Regression-Ordinary Least Square "MLR-OLS" and Multi Linear Regression-Partial Least Square "MLR-PLS") and non-linear (Artificial Neural Network "ANN") models have been built. The MLR-OLS model was disqualified during the training phase since it did not show good results even in the training phase, which could not lead to effective predictions during the validation phase. Then, the performances of MLR-PLS and ANN were evaluated with validation data. Good concentration predictions were obtained in both cases for all the involved analytes. However, in the case of methane, better prediction performances were obtained with ANN, which is consistent with the fact that the MOX sensor's response to CH4 is logarithmic, whereas only linear sensor responses were obtained for the other analytes. Finally, prediction tests performed on one-year aged sensor platforms revealed that PLS model predictions on aged platforms mainly suffered from concentration offsets and that ANN predictions mainly suffered from a drop of sensitivity.
RESUMO
Electrochemical sensors have been used for many decades. However, the modeling of such sensors used in electrolysis mode is poorly documented, especially in the case of multiple gases' parallel actions. These are of great interest since they constitute the first brick to bring information on the natures and concentrations of gaseous mixture compositions, thanks to gray box modeling of sensor arrays, for example. Based on Butler-Volmer's equations, a model assuming parallel reactions at gold cathode has been introduced in this article and confronted with experimental results. The establishment of the model is based on the extraction of three variables: the charge transfer coefficient "α", the reaction order γ, and the reaction constant rate k0. Tests performed without pollutants and with different concentrations of oxygen could be nicely fitted using the model. The influence of the polarization current on the three variables of the model has been evaluated, showing a clear influence on the constant rate and the reaction order. Moreover, increasing the polarization current enabled us to obtain selectivity for oxidant gases. Similarly, the effect of the oxygen concentration was evaluated. Results showed that, in this case, the charge transfer coefficients "α" obtained for oxidant gases are quite different from the ones obtained in the polarization current varying conditions. Therefore, the model will be interesting in situations where polarization current and oxygen content are not varied together. Variation of polarization current can be quite interesting to obtain increased information for multivariate analysis purposes in constant oxygen content situations. Additionally, other parameters have to be considered for applications in which the oxygen content is bound to change, such as exhaust gases or combustion.