Seismic Shifts: A Structural Health Monitoring Textile

Catriona Cheyne, Kirsty McDougall

Research output: Contribution to journalArticlepeer-review

Abstract

This paper describes the fabrication of a novel woven textile with a fully integrated strain-sensitive yarn for application to the built environment as a structural health monitoring system to monitor and ascertain structural damage in real time. The paper presents the context of the use of textiles within the construction industry. It also discusses the strength of using designers as lead researchers in applied science projects, in place of engineers and scientists. The sensor, provided by Nanoforce from Queen Mary University of London, consists of thermoplastic polyurethane fibres containing multi-walled carbon nanotubes extruded as a yarn. This was woven into multiple fabric samples using varying weaves and mix of yarns. The samples were tested for consistency in stability of the conduction of the data. The most stable samples were rewoven and set within a resin skin to form a composite material that could later be applied to a building structure. In this paper we evaluate our methodology firstly by analysing the data taken from the initial samples to establish stability of the data acquisition and ascertain the best weave pattern and choice of yarns. Secondly by applying the weave to a resin skin to explore a viable composite material that could be applied to a construction joint within the building industry.
Original languageEnglish
Pages (from-to)1-24
Number of pages24
JournalJournal of Textile Design Research and Practice
Volume5
Issue number1
DOIs
Publication statusPublished - 1 Mar 2017

Bibliographical note

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Textile Design Research and Practice on 01/03/2017, available online: http://www.tandfonline.com/10.1080/20511787.2016.1275171

Keywords

  • carbon nanotube thread
  • textile
  • composite
  • strain
  • earthquake
  • structural health monitoring system

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