Robust and sensitive frost and ice detection via planar microwave resonator sensor

•High quality factor microwave resonator sensors improve current ice and frost detection techniques.•Frost, ice, and water are detected via the S21 variation of the resonant frequency, resonant amplitude, and quality factor.•The real-time sensors detect frost faster and with higher sensitivity than...

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Veröffentlicht in:Sensors and actuators. B, Chemical Chemical, 2019-12, Vol.301, p.126881, Article 126881
Hauptverfasser: Wiltshire, Benjamin, Mirshahidi, Kiana, Golovin, Kevin, Zarifi, Mohammad H.
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Sprache:eng
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Zusammenfassung:•High quality factor microwave resonator sensors improve current ice and frost detection techniques.•Frost, ice, and water are detected via the S21 variation of the resonant frequency, resonant amplitude, and quality factor.•The real-time sensors detect frost faster and with higher sensitivity than current visual methods.•Fast and accurate detection of both the water-to-ice and ice-to-water phase transitions are demonstrated.•Sensor variation due to temperature can be compensated for to isolate the water, frost, and ice signals. Build up of ice and snow can cause major issues in many industrial and academic endeavors if it is not properly detected and addressed. Ice detection systems are commonly based on visual detection and therefore susceptible to human error and environmental conditions. We introduce a microwave resonator sensor fabricated on a planar substrate operating between 3.5–5 GHz with resonant amplitude −14.5 dB and quality factor of 250. The resonator detects water, frost, and ice based on the measured resonant frequency, amplitude, and quality factor variation in scattering parameter, S21, of the sensor. Three situations are investigated to test the effectiveness of the sensor: first, continuous frost formation on the sensor is tracked and the phenomena of water condensation, frost formation, and subsequent frost growth are characterized. Second, a water droplet is placed on the resonator and frozen, enabling faster and more sensitive detection and representing an initial liquid impact or aggregation on a surface followed by freezing. Lastly, controlled frost formation and removal was performed to better understand the effect of substrate temperature on the sensing parameters so that it could be compensated for via calibration.
ISSN:0925-4005
1873-3077
DOI:10.1016/j.snb.2019.126881