Fatigue Life Estimation of Bridges with Smart Mobile Sensing

Bridge structures experience significant vibrations and repeated stress variations during their lifecycle. These conditions are the bases for fatigue analysis to identify fatigue cracking, which can be used to accurately establish the remaining fatigue life of the structures (i.e., the number of stress cycles before fatigue failure). This is typically achieved through a full-field strain assessment of the fatigue-critical locations of the structure over a typical loading period. Traditional inspection methods collect strain measurements by using strain gauges for fatigue life assessment. Large-scale deployment of wired strain gauges, however, poses a fundamental limitation: they are expensive and laboriously impractical as more spatial information is desired. Addressing these limitations begs for an innovative sensing strategy where information can be integrated from inexpensive data sources. Acceleration data, on the other hand, can be collected relatively inexpensively by means of mobile sensing, which is increasingly an area of interest in many fields of engineering. Mobile sensing eliminates the spatially restrictive nature of fixed sensor networks; the spatial frequency of a mobile sensor network is a direct function of the speed and its sensors' sampling frequencies, as well as the number of mobile devices that can simultaneously collect measurements from the same structure. In this project the authors have developed a deep learning-based methodology that facilitates the use of inexpensively generated structural response data such as accelerations from mobile sensing, to first estimate strain and then subsequently find the remaining fatigue life of a structure and other higher level information that aids in prognosis and decision-making.

• Record URL:
  https://r3utc.psu.edu/files/2021/09/CIAMTIS-LU-CIAM-UTC-REG7_s.pdf
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/58506
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Lehigh University

  Bethlehem, PA  United States  18015

  Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)

  Pennsylvania State University
  University Park, PA  United States  16802

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Pakzad, Shamim N
  • 0000-0003-3127-4453
  • Takac, Martin
  • 0000-0001-7455-2025
• Publication Date: 2021-6-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Photos; References; Tables;
• Pagination: 23p

Subject/Index Terms

• TRT Terms: Acceleration (Mechanics); Bridges; Machine learning; Mobile applications; Service life; Strain (Mechanics)
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01785777
• Record Type: Publication
• Report/Paper Numbers: CIAM-UTC-REG7
• Contract Numbers: 69A3551847103
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Oct 26 2021 11:16AM