MEMS Sensors for Transportation Structures

Non-destructive infrastructure monitoring includes the capability to remotely determine local or global changes in the fundamental character of transportation structures. These changes are nearly always negative and usually occur because of (1) changes in geometry or material continuity from usage distress, and (2) degradation in material properties from corrosion or other environmental factors. Deploying micro-electromechanical systems (MEMS) devices at strategic points within the structure can provide real-time behavioral characteristics of variables including quasi-static deflection, vibration frequency, or wave propagation speed. It has been rather common to accomplish indirect detection of structural character by measuring and interpreting induced motion or vibration of the structure as a result of outside forcing functions. The most common method for doing so has been to use conventional piezoelectric accelerometers, which link mechanical motion to induced electric response, directly wired to data acquisition systems. The challenges of this sort of system are nearly all related to cost: (1) the initial installation and instrumentation, including the necessary wiring, (2) the cost to maintain the system over a reasonable period of time, and 3) the up-front costs of the required equipment. There are alternatives. MEMS cantilevered devices at the micron scale, when optimized to detect these measure associated with structural response, will provide real-time information collected at remote hubs for analysis and synthesis with other health monitoring devices. This approach removes the need for frequent manual inspections and prioritizes decision-making for the most cost-effective remedy. Existing MEMS research focuses on combining these devices with radios and energy harvesting systems to form wireless mesh communications networks for uploading the sensor data, and removing the reliance on batteries. However, such wireless networks place a heavy burden on the integrated device cost and size due to the need for long communications distance and high energy harvesting rates. This proposed effort removes most existing burdens by utilizing connected vehicles as a mobile gateway between the sensors and the remote processing units. Sensors need only communicate across several feet instead of hundreds of feet, which reduces their transmission power, antenna size, energy harvesting requirement, and overall cost. To reduce energy consumption even further, sensors transmit available data only when the excitation from moving vehicles awakens the radio circuits. Implanted MEMS devices monitor structural health factors but may not necessarily measure the impact of pavement roughness on moving vehicles. Therefore, vehicles equipped with GPSvibration sensors to monitor pavement conditions may combine surface roughness measurements with the received MEMs data from their GPS-tagged location. This effort develops the analytical framework and proof-of-concept for utilizing such a combined system of in-situ MEMS sensors and dynamic pavement condition monitoring within a connected vehicle environment. Assessing the effectiveness of this solution will lead to further MEMS design refinement, implementation, and field-testing.

Language

  • English

Project

  • Status: Active
  • Funding: $92000
  • Contract Numbers:

    DTRT12-G-UTC08

  • Sponsor Organizations:

    Research and Innovative Technology Administration

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

    Kline, Robin

  • Performing Organizations:

    Colorado State University

    Department of Civil and Environmental Engineering
    Campus Delivery 1372
    Fort Collins, Colorado  United States  80523
  • Principal Investigators:

    Heyliger, Paul

  • Start Date: 20120101
  • Expected Completion Date: 20161231
  • Actual Completion Date: 0
  • Source Data: MPC-378

Subject/Index Terms

Filing Info

  • Accession Number: 01483290
  • Record Type: Research project
  • Source Agency: Mountain-Plains Consortium
  • Contract Numbers: DTRT12-G-UTC08
  • Files: UTC, RiP
  • Created Date: Jun 6 2013 1:03AM