Assistant Professor Ivan Bartoli, PhD (left) recently received an NSF Civil, Mechanical and Manufacturing Innovation (CMMI) award titled “Remote Infrastructure Monitoring Assessment via Multispectral Imaging of Surface Coatings” in the amount of $430,000 over a period of three years. Co-PIs are MEM Associate Professor Antonios Kontsos, PhD (center) and MEM Assistant Professor Matthew McCarthy, PhD (right).
As infrastructure in the United States continues to age, more efficient and affordable techniques need to be implemented to support monitoring and assessment of these large systems. This research project will test an innovative approach to structural health monitoring of large infrastructure systems such as bridges, railroads, masonry buildings, networks of pipelines, power lines, dams and more.
The project will leverage multispectral imaging (capturing ultraviolet and infrared radiation as well as visible light) of nanofabricated coatings placed on large infrastructure systems (e.g. bridges). Images will be recorded remotely using unmanned aerial vehicles, which are able to survey the system while it is still in use. The sensors that will be embedded on the infrastructure system(s) will be produced using novel manufacturing procedures to design special surface coatings that enable their rapid detection by multispectral sensing and allow accurate deformation measurements.
The multispectral images will be analyzed using dedicated algorithms based on computer vision and photogrammetry. Such algorithms will allow measuring the deformation of the structural system by tracking the relative motion of the coating features and ultimately quantifying position coordinates of critical components of the monitored structures.
Bartoli notes “This novel testing method could provide accurate evaluation of large infrastructure systems without the expensive cost of more traditional large scale testing methods. The coated sensors being developed will bond with the surface of the infrastructure system and their motion will be accurately tracked over time. Combining these innovative sensors with the use of unmanned aerial vehicles provides a method of structural health monitoring that promises to be efficient, reliable, non-invasive, and cost-effective. In order to keep up with the maintenance of today’s aging infrastructure, innovative testing methods such as this need to be developed and perfected.”
If successful, the results of this work would be used to implement structural health monitoring procedures with unprecedented increase in performance. The use of unmanned aerial systems to collect measurements in highly dynamic environments has the potential to radically reduce downtime associated with lengthy and costly maintenance operations. Additionally, they will provide the capability of both earlier and more quantified detection of deterioration and damage.