High Precision Multiple Parameter Measurement Sensor Based on Constitutive Parameters Near-Zero Media

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.

Authors

Institutions

Publication Details

Journal
The Applied Computational Electromagnetics Society Journal (ACES)
Published
2024-08-31
DOI
https://doi.org/10.13052/2024.aces.j.390804
Primary Topic
Advanced MEMS and NEMS Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High Precision Multiple Parameter Measurement Sensor Based on Constitutive Parameters Near-Zero Media

Qiao Yu Li, Yuliang Mao, Yuxuan Zhou
The Applied Computational Electromagnetics Society Journal (ACES)
Advanced MEMS and NEMS Technologies
article

High Precision Multiple Parameter Measurement Sensor Based on Constitutive Parameters Near-Zero Media

Qiao Yu Li, Yuliang Mao, Yuxuan Zhou
article en

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.

The Applied Computational Electromagnetics Society Journal (ACES)
Shanghai University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 79%
Advanced MEMS and NEMS Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.