Full Content is available to subscribers

Subscribe/Learn More  >

Localized Damage Identification of Plate-Like Structures With Time-Delayed Binary Data From a Self-Powered Sensor Network

[+] Author Affiliations
Hadi Salehi, Rigoberto Burgueño, Saptarshi Das, Subir Biswas

Michigan State University, Lansing, MI

Shantanu Chakrabartty

Washington University in St. Louis, St. Louis, MO

Paper No. SMASIS2017-3941, pp. V002T05A008; 9 pages
  • ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
  • Volume 2: Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation; Structural Health Monitoring
  • Snowbird, Utah, USA, September 18–20, 2017
  • Conference Sponsors: Aerospace Division
  • ISBN: 978-0-7918-5826-4
  • Copyright © 2017 by ASME


Recent advances in energy harvesting technologies have led to the development of self-powered monitoring techniques that are energy-efficient. This study presents an intelligent damage identification strategy for plate-like structures based on the data provided by a network of self-powered sensors that communicate through a pulse switching protocol, which has been demonstrated as an effective means for minimizing communication energy demands. The energy-aware pulse switching communication architecture uses single pulses instead of multi-bit packets for information delivery, resulting in discrete binary data. A system employing such an energy-efficient technology requires dealing with power budgets for sensing and communication of binary data, which leads to time delay constraints. In this paper, a novel machine learning framework incorporating low-rank matrix decomposition, pattern recognition, and a statistical approach is proposed to overcome challenges inherent in algorithm design for damage identification using time-delayed binary data. Performance and effectiveness of the proposed energy-aware damage identification strategy was examined for the case of a dynamically loaded plate. Damage states were simulated on a finite element model by reducing stiffness in a region of the plate. Results show that the presence and location of the damage can be effectively identified even with noisy features and missing data. The performance and applicability of the proposed localized damage detection strategy for plate-like structures using discrete time-delayed binary data from a novel wireless sensor network is thus demonstrated.

Copyright © 2017 by ASME



Interactive Graphics


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

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