Abstract
A high-precision multiple parameter measurement sensor based on constitutive parameters near-zero (CPNZ) media has been proposed, which can effectively and accurately predict changes in temperature and relative humidity simultaneously and independently. The dual-channel microwave sensor is composed of a double doping CPNZ substrate integrated waveguide (SIW) cavity, which has the capability to predict different parameters independently. A multi-input and multi-output model is constructed to improve the measurement accuracy by training back propagation (BP) neural network. The relative error of the predicted temperature is smaller than 1.3%, with mean square error (MSE) of ±0.15. The relative error of the predicted relative humidity is smaller than 8.74%, with MSE of ±0.1. The multiple parameter sensor based on CPNZ materials offers a promising platform for multiple parameter sensing research, providing essential technical support and infrastructure for the development of fields like the Internet of Things, intelligent manufacturing, and smart cities.
Published Version
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