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Intelligent Sensing Using Multiple Sensors for Material Characterization.

Ali M Albishi1, Seyed H Mirjahanmardi2, Abdulbaset M Ali3

  • 1Department of Electrical Engineering, King Saud University, Riyadh 11451, Saudi Arabia. aalbishi@KSU.EDU.SA.

Sensors (Basel, Switzerland)
|November 6, 2019
PubMed
Summary

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This summary is machine-generated.

This study introduces an intelligent sensing method using microwave near-field sensors to precisely measure material properties like fluid concentration. The technique modulates sensor frequency responses, achieving high accuracy even with limited data via neural networks.

Area of Science:

  • Microwave Engineering
  • Sensors and Transducers
  • Material Characterization

Background:

  • Accurate material parameter extraction is crucial for various industrial applications.
  • Traditional sensing methods may face limitations in precision and data requirements.
  • Developing intelligent sensing techniques can enhance measurement capabilities.

Purpose of the Study:

  • To present a novel intelligent sensing technique for material parameter characterization.
  • To utilize modulated frequency responses of microwave near-field sensors.
  • To apply neural networks for accurate analysis of sensor data.

Main Methods:

  • Modulating frequency responses of multiple microwave near-field sensors.
  • Analyzing sensor responses over a wide frequency band as high-dimensional vectors.
Keywords:
artificial intelligencecomplementary split-ring resonatorselectrically-small resonatorsfluid characterizationmaterial measurementsneural networkssensors

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  • Employing neural networks for model generalization with small datasets.
  • Designing a microwave sensing system with planar resonators.

    • Main Results:

    • Demonstrated a microwave sensing system for fluid concentration detection.
    • Achieved very high accuracy in characterizing fluid material composition.
    • Validated the effectiveness of the intelligent sensing concept.

    Conclusions:

    • The proposed intelligent sensing technique offers a highly accurate method for material characterization.
    • Modulating microwave sensor frequency responses combined with neural networks is effective.
    • This approach shows promise for applications requiring precise material analysis.