期刊
IEEE SENSORS JOURNAL
卷 21, 期 5, 页码 5798-5808出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2020.3036736
关键词
Sensors; Strain; Tomography; Strain measurement; Conductivity; Voltage measurement; Monitoring; Electrical Impedance Tomography (EIT); hyperparameter; Montgomery method; strain sensor; Structural Health Monitoring (SHM)
资金
- Christian Doppler Research Association
- Austrian Federal Ministry for Digital and Economic Affairs
- National Foundation for Research, Technology and Development
This paper introduces a method to measure strain through 2D Electrical Impedance Tomography (EIT) combined with a planar elastoresistive sensor, allowing simultaneous and spatial strain and damage monitoring by a single sensor. The importance of selecting a suitable hyperparameter for the EIT reconstruction algorithm is discussed, with a selection approach based on the combinational use of the L-Curve (LC) method and the Fixed Noise Figure (NF) method.
A commonly used parameter in Structural Health Monitoring (SHM) to ensure the reliability and structural integrity of a lightweight structure is the mechanical strain. Usually, a strain gauge is the standard solution to measure local strain. The aim of this paper is to measure strain through two-dimensional Electrical Impedance Tomography (2D EIT) in combination with a planar elastoresistive sensor. Thereby, the quantitative value of the conductivity change as a function of strain is reconstructed. The advantage of this method compared to a conventional strain gauge is that the EIT allows simultaneous and spatial strain and damage monitoring by a single sensor. In the presented test setup, the sensor is bent uniformly over the sensor surface and the calculated EIT results are verified by using the Montgomery method. The article presents the main steps for strain measurement using 2D EIT, starting with an appropriate derivation of a Finite Element (FE) model of the sensor as well as the measurement data processing. Furthermore, the selection of the hyperparameter, which controls the EIT reconstruction algorithm, is presented. The selection of a suitable hyperparameter is essential for the reconstruction of actual conductivity values. The presented selection approach is based on the combinational use of the L-Curve (LC) method and the fixed Noise Figure (NF) method.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据