A Review on Microwave Resonant Sensors

ZHAO Wen-sheng; FANG Yu-hao; WANG Da-wei; LIU Jun

doi:10.12263/DZXB.20220124

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A Review on Microwave Resonant Sensors

SURVEYS AND REVIEWS | 更新时间：2025-12-08

- A Review on Microwave Resonant Sensors
- ACTA ELECTRONICA SINICA Vol. 50, Issue 10, Pages: 2530-2541(2022)
- 作者机构：
  
  杭州电子科技大学电子信息学院，浙江省大规模集成电路设计重点实验室，浙江杭州 310018
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20220124
  CLC： TN61;
- Received：29 January 2022，
  
  Revised：2022-05-26，
  
  Published：25 October 2022
- 稿件说明：
移动端阅览
赵文生,方宇浩,王大伟等.微波谐振式传感器研究进展[J].电子学报,2022,50(10):2530-2541.

ZHAO Wen-sheng,FANG Yu-hao,WANG Da-wei,et al.A Review on Microwave Resonant Sensors[J].ACTA ELECTRONICA SINICA,2022,50(10):2530-2541.
赵文生,方宇浩,王大伟等.微波谐振式传感器研究进展[J].电子学报,2022,50(10):2530-2541. DOI： 10.12263/DZXB.20220124.

ZHAO Wen-sheng,FANG Yu-hao,WANG Da-wei,et al.A Review on Microwave Resonant Sensors[J].ACTA ELECTRONICA SINICA,2022,50(10):2530-2541. DOI： 10.12263/DZXB.20220124.

摘要

微波谐振式传感器具有低成本、高灵敏度、实时、无损检测等特点，在生物、医疗、环境等领域都有着广阔的应用前景.一般来说，微波谐振式传感器通过传输线激励谐振单元，通过谐振频率偏移等特征变化获得待测量.本文对微波谐振式传感器现有研究成果进行了详细的综述.首先简要介绍了微波谐振式传感器分类、基本工作原理及关键性能指标，其次以位移传感器、介质传感器及液体传感器这3种类型总结当前微波谐振式传感器国内外研究进展，之后着重探讨了群智能算法、机器学习等优化算法在微波谐振式传感器优化设计方面的应用，最后展望了微波谐振式传感器的发展前景以及存在的挑战.

Abstract

Microwave resonant sensors have the characteristics of low-cost

high-sensitivity

real-time and non-destructive detection. They have broad application prospects in various fields including biological

medical

and environmental. Generally speaking

microwave resonant sensor is composed of a resonant unit excited by transmission line. The quantity to be measured is obtained by the characteristic changes such as shift in resonant frequency. In this paper

the existing research of microwave resonant sensors are reviewed in detail. Firstly

the classification

basic operating principle

and key performance indicators of microwave resonant sensors are briefly introduced. Secondly

the current domestic and abroad research progresses of microwave resonant sensors are summarized in three types of sensors

i.e.

displacement sensors

dielectric sensors

and liquid sensors. Then

the applications of optimization algorithms such as swarm intelligence algorithms and machine learning on the optimal design of microwave resonant sensors are emphatically explored. Finally

the future development prospects and existing challenges of microwave resonant sensors are discussed.

关键词

Keywords

references

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