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Microwave Based Sensor for Detecting Water in Alcohol

  • Markku Oksanen
  • Heikki Räikkönen
Chapter

Abstract

The detection of minute amounts of water in any fuel-based system is important. Its presence in a large underground tank might be a sign of a leak where fuel is flowing into the water table and causing an environmental problem. A simple and effective means of real time monitoring of small concentrations of dissolved water in fuel tanks is therefore needed. Due to their polar molecular structure both water and many hydrocarbons readily absorb 2 GHz microwave radiation. This singular phenomena can be used to detect water concentrations in hydrocarbon solutions by modulating the microwave field and detecting the thermal effect by means of a modification of the photoacoustic cell method [1], Although hydrocarbons, as well as water, possess microwave absorption properties, the overall effect when thermal properties are taken into account allows for the detection of water. The emitted acoustic signal amplitude is dependent on thermal properties of the fluid. These properties are a function of relative concentrations of the components in a two fluid system. A relation between component concentration and acoustic emission amplitude can be found and this phenomena can be used in detection of one of the components. In the system presented here the fluid is applied to a stripline microwave transmission line and forms the high loss dielectric in the transmission line. The emitted acoustic signal is monitored with an attached polyvinyldedrafluoride (PVDF) microphone in the form of a PVDF foil fastened to the detector cell. This detector can be be made submersible and can stay in the tank for continuous monitoring. Essentially, our system is a single frequency microwave spectroscopy based detector which is tuned to the amplitude modulation frequency of the microwave excitation.

Keywords

Acoustic Signal Microwave Absorption Microwave Absorption Coefficient Strip Line Acoustic Emission Amplitude 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Plenum Press, New York 1995

Authors and Affiliations

  • Markku Oksanen
    • 1
  • Heikki Räikkönen
    • 1
  1. 1.Department of PhysicsUniversity of HelsinkiHelsinkiFinland

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