A Temperature-Compensated High-Resolution Microwave Sensor Using Artificial Neural Network
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https://ieeexplore.ieee.org/document/9163236
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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%.
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http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/version/c_b1a7d7d4d402bcce http://purl.org/coar/version/c_71e4c1898caa6e32
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en