Simultaneous measurement of time‐of‐wetness and electrolyte concentrations with IDE sensors by evaluation of impedance spectra using an artificial neural network

• Published in: Materials and corrosion Vol. 73; no. 2; pp. 189 - 195
• Main Authors: Wagner, Benjamin, Mittelbach, Andreas, Geiß, Paul L.
• Format: Journal Article
• Language: English
• Published: Weinheim Wiley Subscription Services, Inc 01.02.2022
• Subjects: Artificial neural networks; electrolyte concentration; Electrolytes; Impedance; impedance spectroscopy; interdigitated electrodes; Moisture content; neural network; Neural networks; Sensors; Sodium chloride; Time measurement; time‐of‐wetness
• ISSN: 0947-5117; 1521-4176
• DOI: 10.1002/maco.202112714

A measurement principle to examine the time‐of‐wetness and concentration of electrolytes using interdigitated electrode sensors and a neural network approach is discussed in this study. The electrolyte serves as a capacitive and resistive medium and changes the frequency responses of the sensor depending on its surface coverage and concentration. The measured impedance spectra are analyzed by an artificial neural network (ANN) model, which was trained by experimental and simulated data. Investigations of the performance of the ANN show a precise determination of the electrolyte concentration and present surface coverage. Furthermore, the application of this fast and easy method is discussed and tested to investigate the drying behavior of droplets from aqueous sodium chloride solution on the sensor surface in a climate chamber. To examine the time‐of‐wetness and electrolyte concentrations simultaneously with interdigitated electrode sensors, impedance spectra are evaluated using an artificial neural network model. This easy, fast, and precise method is used to investigate the drying behavior of condensed electrolyte on the sensor surface after a salt spray phase in a climate chamber.