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Iowa State University--Becoming the Best

Autonomous Sensing Skin for Detection and Localization of Fatigue Cracks


Principal investigator:

Co-principal investigators:

Project status

In progress

Start date: 01/09/14
End date: 08/31/18



Partner(s): University of Kansas and KSDOT

About the research


Early detection of possible defects in civil infrastructure is vital to ensuring timely maintenance and extended life expectancy. A common structural problem for bridges is the growth of fatigue cracks in steel members. While these cracks can be detected using nondestructive evaluation (NDE) techniques, automating the monitoring process would result in substantial savings in repair costs, and enhanced structural health and safety. This process is known as structural health monitoring (SHM). Existing SHM techniques are not suitable for monitoring of fatigue cracks. For instance, off-the-shelf strain gauges are small and can only be installed at specific locations, and are therefore incapable of detecting new fatigue cracks. Indirect methods exist for diagnosing new fatigue cracks from strain gauges or accelerometers, but these techniques also fail at crack localization. It follows that there is a need to develop a low-cost autonomous sensing solution capable of detecting and localizing fatigue cracks.