Performance evaluation of experimental damage detection in structure health monitoring using acceleration

Mohamed Elsersy, Khalid Abualsaud, Tarek Elfouly, Mohamed Mahgoub, Mohamed Ahmed, Marwa Ibrahim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Wireless sensor networks (WSNs) are one of the emerging technologies in the 21st century. In the structural health monitoring (SHM). WSNs are used as one of the vitally capable technologies in the SHM. The accelerometer module in the existing sensor nodes enables several novel applications. In this paper, a prototype for monitoring and detecting the damage for the real bridge using these sensor nodes is built. The prototype consists of sensor nodes, shaking table including its amplifier, and real bridge. The sensors are placed on a scaled down concrete bridge model that is mounted on a shaking table. The results are demonstrated in terms of acceleration on different nodes at a particular excitation frequency in the case of normal, single-side damage, and double-side damage.

Original languageEnglish (US)
Title of host publication2016 International Wireless Communications and Mobile Computing Conference, IWCMC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages529-534
Number of pages6
ISBN (Electronic)9781509003044
DOIs
StatePublished - Sep 26 2016
Event12th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2016 - Paphos, Cyprus
Duration: Sep 5 2016Sep 9 2016

Publication series

Name2016 International Wireless Communications and Mobile Computing Conference, IWCMC 2016

Other

Other12th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2016
Country/TerritoryCyprus
CityPaphos
Period9/5/169/9/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Keywords

  • Acceleration
  • Data acquisition
  • Data processing
  • Structural health monitoring
  • Vibration
  • Wireless sensor networks

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