Design Optimization of a Multiphase Coplanar Capacitive Sensor

Mahmoud Altrabolsi, Mahdi Saleh, Imad H. Elhajj, Daniel Asmar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

Detecting oil under the ice in arctic regions with current remote sensing techniques is challenging due to several factors, such as the attenuation of radio-frequency electromagnetic waves and the unknown properties of oil that vary depending on its type and the environmental conditions. To address this problem, we propose a planar capacitive sensor that works in the quasi-electrostatic domain to detect and characterize oil under ice based on its dielectric properties. This paper focuses on the design optimization process that was conducted with the aim of improving the sensitivity and penetration depth of our proposed sensor. Our design optimization process studies different geometrical and electrical parameters and compares the sensor performance obtained from using grounded (passive) backplanes and driven (active) guards. It includes a set of simulations performed using ANSYS electrostatic simulation software and a set of experiments performed under indoor laboratory conditions. The results demonstrated the effectiveness of the optimized sensor design, which is based on a pair of trapezoidal electrodes that are implemented on separate PCBs and surrounded by driven guards. Another major novelty of our proposed sensor design is based on measuring the mutual capacitance between the two sensor plates after changing the horizontal distance between them using a dynamic mounting setup. This allows us to take a number of capacitance measurements at different penetration depths of the electric field before using them to detect the presence of oil and estimate its thickness. Further tests in real-world scenarios are planned for future work.
Original languageEnglish
Title of host publication2023 IEEE International Conference on Imaging Systems and Techniques (IST)
PublisherIEEE
Number of pages6
DOIs
Publication statusPublished - 20 Dec 2023

Keywords

  • Capacitive Sensing
  • Electric Field Sensing
  • Oil Spill

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