0

Full Content is available to subscribers

Subscribe/Learn More  >

Structural Health Monitoring of Truss Type Structures Using Statistical Approach

[+] Author Affiliations
Mahdi Saffari, Ramin Sedaghati

Concordia University, Montreal, QC, Canada

Ion Stiharu

Concordia Univiversity, Montreal, QC, Canada

Paper No. SMASIS2014-7486, pp. V001T05A002; 7 pages
doi:10.1115/SMASIS2014-7486
From:
  • ASME 2014 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
  • Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring; Keynote Presentation
  • Newport, Rhode Island, USA, September 8–10, 2014
  • Conference Sponsors: Aerospace Division
  • ISBN: 978-0-7918-4614-8
  • Copyright © 2014 by ASME

abstract

This paper proposes an effective statistical based vibration health monitoring technique using Auto Regressive (AR) parameters and Support Vector Machine (SVM) for truss type structures. The finite element method has been utilized to obtain acceleration response signals of a space truss structure under random excitations. The signals are then processed to extract their AR parameters as the feature vectors in which the AR parameters of the healthy structure are considered to be the reference baseline data. A Damage Index is then defined to be the standard deviation of the feature vectors from the baseline data. The proposed index provides an effective tool to detect the damage in the structure. It is shown that using only one sensor, it is still possible to accurately detect the damage.

To locate the damage, data classification technique based on Support Vector Machine (SVM) has been employed. It is shown that SVM can successfully classify different signals extracted from the structure. Finally extensive sensitivity analysis has been performed to study the effect of different parameter such as crack size, number of sensors and AR parameter numbers on the accuracy of detection and localization processes.

Copyright © 2014 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In