Automatic classification and permittivity estimation of glycerin solutions using a dielectric resonator sensor and machine learning techniques

M. Monteagudo Honrubia, F.J. Herraiz-Martínez, J. Matanza

IEEE International Instrumentation and Measurement Technology Conference - I2MTC 2023, Kuala Lumpur (Malaysia). 22-25 May 2023

Summary:

This paper presents the application of a dielectric resonator sensor to characterize glycerin solutions. Air and nine different concentrations were measured within a relative permittivity range from 1 to 78.3. Principal Component Analysis (PCA) and Support Vector Machine (SVM) were used to perform automatic classification with an 100% accuracy and the regression of both concentration and permittivity with a RMSE of 0.34% and 0.287 respectively.

Keywords: Dielectric resonator, microwave sensor, machine learning, dielectric characterization, glycerin purification

DOI: https://doi.org/10.1109/I2MTC53148.2023.10176097

Published in I2MTC 2023, pp: 1-5, ISBN: 978-1-6654-5384-4

Publication date: 2023-07-13.

Citation:
M. Monteagudo Honrubia, F.J. Herraiz-Martínez, J. Matanza, Automatic classification and permittivity estimation of glycerin solutions using a dielectric resonator sensor and machine learning techniques, IEEE International Instrumentation and Measurement Technology Conference - I2MTC 2023, Kuala Lumpur (Malaysia). 22-25 May 2023. In: I2MTC 2023: Conference proceedings, ISBN: 978-1-6654-5384-4