4.7 Article

On the Capability of Measuring Actual Strain Values With Electrical Impedance Tomography Using Planar Silkscreen Printed Elastoresistive Sensors

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

  1. Christian Doppler Research Association
  2. Austrian Federal Ministry for Digital and Economic Affairs
  3. National Foundation for Research, Technology and Development

向作者/读者索取更多资源

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.

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