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Sensitivity improvement of MWCNTs/epoxy composite strain sensor

  • Mun Young Hwang
  • , Myeongcheol Kang
  • , Lae Hyong Kang*
  • *Corresponding author for this work

Research output: Contribution to conferenceConference paperpeer-review

Abstract

We investigated the optimal manufacturing conditions for a multi-walled carbon nanotubes (MWCNTs)/epoxy composite strain sensor in order to improve the sensitivity of the sensor. The specimens were manufactured and the electrical properties of the specimens were compared according to different MWCNT concentrations and dispersion methods. The sensitivity of MWCNTs/epoxy composite strain sensor was investigated quantitatively by measuring resistance changes according to the variation of a constant strain. Scanning electron microscopy (SEM) images confirmed that MWCNTs/epoxy composites with different CNT concentrations have a good homogeneity and dispersion. In addition, we attempted to evaluate the sensing characteristics and compared them with those of a conventional foil strain gauge. A MWCNTs/epoxy composite was attached to an acrylic beam. The response of the MWCNTs/epoxy sensor was fairly good, and the result was nearly identical to that of the strain gauge. In order to verify the performance of the sensor, a Wheatstone bridge circuit and a signal conditioning circuit were used. This current study on the sensitivity of MWCNTs/epoxy composite sensors provides a useful tool for designing smart sensing and multifunctional polymer composites. The concept of using these conductive fillers provides a low-cost and effective way to fabricate piezoresistive polymer nanocomposites for structural health monitoring applications.

Original languageEnglish
Title of host publicationStructural Health Monitoring 2017
Subtitle of host publicationReal-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
EditorsFu-Kuo Chang, Fotis Kopsaftopoulos
PublisherDEStech Publications
Pages1953-1960
Number of pages8
ISBN (Electronic)9781605953304
DOIs
StatePublished - 2017
Event11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017 - Stanford, United States
Duration: 2017.09.122017.09.14

Publication series

NameStructural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
Volume2

Conference

Conference11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017
Country/TerritoryUnited States
CityStanford
Period17.09.1217.09.14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems
  • Data Science

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