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基于铌酸锂的用于结构健康监测的新型表面声波温度应变传感器

Novel Surface Acoustic Wave Temperature-Strain Sensor Based on LiNbO for Structural Health Monitoring.

作者信息

Li Xiangrong, Tan Qiulin, Qin Li, Yan Xiawen, Liang Xiaorui

机构信息

State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.

Science and Technology on Electronic Test and Measurement Laboratory, North University of China, Taiyuan 030051, China.

出版信息

Micromachines (Basel). 2022 Jun 9;13(6):912. doi: 10.3390/mi13060912.

DOI:10.3390/mi13060912
PMID:35744526
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9227228/
Abstract

In this paper, we present the design of an integrated temperature and strain dual-parameter sensor based on surface acoustic waves (SAWs). First, the COMSOL Multiphysics simulation software is used to determine separate frequencies for multiple sensors to avoid interference from their frequency offsets caused by external physical quantity changes. The sensor consists of two parts, a temperature-sensitive unit and strain-sensitive unit, with frequencies of 94.97 MHz and 90.05 MHz, respectively. We use standard photolithography and ion beam etching technology to fabricate the SAW temperature-strain dual-parameter sensor. The sensing performance is tested in the ranges 0-250 °C and 0-700 μԑ. The temperature sensor monitors the ambient temperature in real time, and the strain sensor detects both strain and temperature. By testing the response of the strain sensor at different temperatures, the strain and temperature are decoupled through the polynomial fitting of the intercept and slope. The relationship between the strain and the frequency of the strain-sensitive unit is linear, the linear correlation is 0.98842, and the sensitivity is 100 Hz/μԑ at room temperature in the range of 0-700 μԑ. The relationship between the temperature and the frequency of the temperature-sensitive unit is linear, the linearity of the fitting curve is 0.99716, and the sensitivity is 7.62 kHz/°C in the range of 25-250 °C. This sensor has potential for use in closed environments such as natural gas or oil pipelines.

摘要

在本文中,我们展示了一种基于表面声波(SAW)的集成温度和应变双参数传感器的设计。首先,使用COMSOL Multiphysics模拟软件来确定多个传感器的单独频率,以避免外部物理量变化引起的频率偏移干扰。该传感器由两部分组成,一个温度敏感单元和一个应变敏感单元,频率分别为94.97 MHz和90.05 MHz。我们采用标准光刻和离子束蚀刻技术来制造SAW温度 - 应变双参数传感器。在0 - 250°C和0 - 700 με范围内测试传感性能。温度传感器实时监测环境温度,应变传感器可同时检测应变和温度。通过测试应变传感器在不同温度下的响应,通过截距和斜率的多项式拟合来解耦应变和温度。应变敏感单元的应变与频率之间的关系是线性的,线性相关性为0.98842,在0 - 700 με范围内室温下的灵敏度为100 Hz/με。温度敏感单元的温度与频率之间的关系是线性的,拟合曲线的线性度为0.99716,在25 - 250°C范围内的灵敏度为7.62 kHz/°C。这种传感器有潜力用于天然气或石油管道等封闭环境。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/2622d63ee909/micromachines-13-00912-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/dc32c4d1e781/micromachines-13-00912-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/b85737efd5f8/micromachines-13-00912-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/efb6f8473cf1/micromachines-13-00912-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/5d601f1c0609/micromachines-13-00912-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/5b97d01aa5e5/micromachines-13-00912-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/29424539ef21/micromachines-13-00912-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/338ff9e80ed2/micromachines-13-00912-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/2622d63ee909/micromachines-13-00912-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/dc32c4d1e781/micromachines-13-00912-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/b85737efd5f8/micromachines-13-00912-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/efb6f8473cf1/micromachines-13-00912-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/5d601f1c0609/micromachines-13-00912-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/5b97d01aa5e5/micromachines-13-00912-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/29424539ef21/micromachines-13-00912-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/338ff9e80ed2/micromachines-13-00912-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b8c/9227228/2622d63ee909/micromachines-13-00912-g008.jpg

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