文章摘要
李鹏旭,李红浪,程利娜,卢孜筱,罗为,刘久玲.一种高灵敏度的桥型声表面波应变传感器*[J].,2021,40(2):237-242
一种高灵敏度的桥型声表面波应变传感器*
A high sensitivity bridge surface acoustic wave strain sensor
投稿时间:2020-06-06  修订日期:2021-03-02
中文摘要:
      为了提高声表面波传感器应变灵敏度,该文 提出了一种桥型声表面波应变传感器。首先根据受压弯曲构件中应变分布特点设计了桥型声表面波应变传感器,并建立有限元模型,结合微扰法分析了桥型结构几何参数与声表面波应变传感器灵敏度的关系。根据分析结果确定桥型声表面波应变传感器几何结构参数,并与传统声表面波应变传感器的应变灵敏度进行了对比研究,在此基础上搭建受压弯曲微动平台开展实验研究,结果表明:在直梁构件受压弯曲应变测量时,Y34°切向的桥型声表面波应变传感器的应变灵敏度为1692 Hz/με,传统声表面波传感器应变灵敏度为1328 Hz/με,桥型声表面波应变传感器的应变灵敏度较传统声表面波应变传感器有明显提高。
英文摘要:
      In this paper, a bridge surface acoustic wave (SAW) strain sensor is proposed to improve the strain sensitivity of the SAW strain sensor. First, a bridge SAW strain sensor is designed based on the characteristics of the strain distribution in the straight beam under bending. The finite element model of the bridge SAW strain sensor is established, and the relationship between the geometric parameters of the bridge structure and the sensitivity of the SAW strain sensor is analyzed combined with the perturbation method. Then the geometric structure parameters are determined according to the analysis results, and the strain sensitivities of the bridge SAW strain sensor and traditional SAW strain sensor are compared and analyzed in detail. Eventually, a micro-motion platform is built to carry out the experimental research. The results indicates that, the strain sensitivity under bending compression of the Y34° cut bridge SAW sensor is 1692 Hz/με, while that of the traditional SAW sensor is 1328 Hz/με. The sensitivity of the bridge SAW strain sensor is significantly improved compared to the traditional sensor.
DOI:10.11684/j.issn.1000-310X.2021.02.009
中文关键词: 声表面波  应变传感器  受压弯曲  桥型结构  应变灵敏度
英文关键词: surface acoustic wave  strain sensor  bend deformation  bridge structure  strain sensitivity
基金项目:国家重点基础研究发展计划(973计划)
作者单位E-mail
李鹏旭 中国科学院声学研究所 lipengxu@mail.ioa.ac.cn 
李红浪* 国家纳米科学中心 lhl@nanoctr.cn 
程利娜 中国科学院声学研究所 chenglina@mail.ioa.ac.cn 
卢孜筱 国家纳米科学中心 luzx2019@nanoctr.cn 
罗为 华中科技大学 luowei@mail.hust.edu.cn 
刘久玲 中国科学院声学研究所 liujiuling@mail.ioa.ac.cn 
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