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.

中文翻译：

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通过使用人工神经网络评估阻抗谱，使用 IDE 传感器同时测量湿润时间和电解质浓度

本研究讨论了使用叉指电极传感器和神经网络方法检查电解质的湿润时间和浓度的测量原理。电解质充当电容和电阻介质，并根据其表面覆盖范围和浓度改变传感器的频率响应。测量的阻抗谱通过人工神经网络 (ANN) 模型进行分析，该模型通过实验和模拟数据进行训练。对人工神经网络性能的研究显示了电解质浓度和当前表面覆盖率的精确测定。此外，讨论和测试了这种快速简便的方法的应用，以研究气候室中传感器表面氯化钠水溶液中液滴的干燥行为。