Arrangement of Sensors and Probability of Detection for Sensing Sheets Based on Large-Area Electronics for Reliable Structural Health Monitoring

The large area electronics (LAE) sensing sheet contains dense array of individual sensors, but there are some non-instrumented spaces between the sensors that are not sensitive to strain anomalies. In addition, individual sensors are sensitive to strain in one specific direction, while the damage (e.g. cracking of concrete and bowing of steel), can generate strain field anomalies that do not necessarily occur in the same direction. If the sensor network is not design correctly, all these effects can potentially lead to unsuccessful damage identification. To address the above challenges, probabilistic approaches are needed to establish a sensor network within LAE based on the probability that this particular network can detect damage of a certain size (probability of detection). Thus, the objective of this project is to create methodology for design of sensor network for LAE sensing sheets that will enable reliable identification of damage of a given size. The methodology will be based on probabilistic approach, and it will take into account the size of the LAE sensing sheet, size of the individual sensor, angular sensitivity of the sensor to damage, and orientation and size of the damage.

Language

  • English

Project

  • Status: Active
  • Funding: $144418.00
  • Contract Numbers:

    DTRT13-G-UTC28

    CAIT-UTC-NC7

  • Sponsor Organizations:

    New Jersey Department of Transportation

    1035 Parkway Avenue
    Trenton, NJ  United States  08625

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue
    Washington, DC  United States  20590
  • Project Managers:

    Kasbekar, Nagnath

    Szary, Pat

  • Performing Organizations:

    Princeton University

    Princeton, NJ  United States  08540
  • Principal Investigators:

    Glisic, Branko

  • Start Date: 20140201
  • Expected Completion Date: 0
  • Actual Completion Date: 20160131
  • Source Data: RiP Project 36993

Subject/Index Terms

Filing Info

  • Accession Number: 01534437
  • Record Type: Research project
  • Source Agency: Center for Advanced Infrastructure and Transportation
  • Contract Numbers: DTRT13-G-UTC28, CAIT-UTC-NC7
  • Files: UTC, RiP
  • Created Date: Aug 13 2014 1:00AM