A Temperature-Compensated High-Resolution Microwave Sensor Using Artificial Neural Network

• Author(s) / Creator(s)

  • Kazemi, Nazli
  • Abdolrazzaghi, Mohammad
  • Musilek, Petr

• In this study, a loss-compensated microwave (MW) planar sensor is used to characterize fluids at ~1 GHz. The environmental temperature is shown to adversely impact the recorded resonance frequency of the MW sensor, leading to data mixing. This issue is resolved using a feedforward artificial neural network with two hidden layers. Various concentrations of methanol in water (0%–100% with 10% increments) are measured at temperatures ranging between 22°C and 60°C. This smart sensor system exhibits a strong ability to discriminate the correct data regardless of erroneous interfering factors up to 92%.

• Date created

  2020-01-01

• Subjects / Keywords

  • artificial neural network
  • machine learning
  • microwave sensor
  • split-ring resonator (SRR)
  • temperature compensation

• Type of Item

  Article (Draft / Submitted)

• DOI

  https://doi.org/10.7939/r3-gm2w-tn25

• License

  Attribution-NonCommercial 4.0 International