It is often stated that well-constructed structures possess “great legs.” However, how can an inspector determine if a structure or bridge has compromised support?
In the medical field, doctors rely on X-rays for patient diagnosis, and now, local scientists aspire to provide engineers with similar monitoring capabilities. To enhance the supervision of structures and bridges, researchers at the University of Central Florida are developing virtual reality and artificial intelligence tools.
In 2019, the United States ranked 13th globally for its aging infrastructure, as reported by the World Economic Forum. The American Society of Civil Engineers evaluated the nation’s infrastructure in 2021, underscoring the necessity for advanced technologies to effectively monitor and upkeep its structures, bridges, and roads.
Necati Catbas, a professor at UCF, aims to address this need by devising four unique solutions. Collaborating with a team of UCF undergraduates and students, he envisions that their innovations will empower engineers to scrutinize structures akin to medical professionals.
Catbas, a distinguished Lockheed Martin St. Laurent professor, elucidates, “Rather than observing the structure as a whole, you delve into its individual components, much like utilizing MRI or X-ray technology to gain profound insights.”
The University of Central Florida
A visual summary of an AR-assisted assessment framework aids in evaluating data for an initial design review.
Among the technologies pioneered by UCF researchers is “Computer vision,” which enables the detection of system anomalies imperceptible to human auditors. By donning headphones linked to sensors embedded within a structure, users can monitor the displacement and vibrations of support beams. Through mixed reality, users can interact with detected cracks and simulate potential structural alterations.
Distinct from physical inspections, computer vision facilitates visual scrutiny of structural integrity without necessitating direct access to the structures, proving valuable for inspectors.
Catbas emphasizes, “Current inspection practices heavily rely on visual assessments and the expertise of inspectors, supplemented by evolving technologies.”
A separate tool, the conceptual adversarial network, empowers users to predict the potential deformations or fractures in newer structures by leveraging historical data from analogous older structures.
“We extract novel insights from existing data, essentially generating synthetic data to forecast structural changes based on sophisticated algorithms,” explains Catbas.
Furthermore, the UCF team has devised an immersive visualization system that enables remote “virtual tours” of structures or bridges using virtual reality technology. Users can observe real-time structural conditions within a computer-simulated environment overlaid with VR data.
The University of Central Florida
Utilizing hand gestures for input, the photogrammetry model calculates the volume of a natural object accurately.
Catbas describes the experience as akin to embarking on a virtual bridge tour, providing users with enhanced mobility to explore the structure and its data.
Moreover, artificial intelligence is integrated into the collective knowledge platform to streamline inspection processes. Inspectors equipped with helmets or handheld devices can assess damaged areas in real time, eliminating the need for manual measurements and gaining insights into the structure’s condition.
Catbas underscores the importance of efficient data management and comprehension within complex data domains as the primary objectives of these advancements.
While these innovative structural technologies are poised for integration into engineering standards, Catbas notes that regulatory committees nationwide must first review and approve them for routine engineering and inspection applications.
Highlighting the evolving role of technology in the American infrastructure, Catbas envisions leveraging these advancements not only for individual bridge assessments but also to aid communities in post-disaster recovery efforts.
“These technologies can help identify critical links within our neighborhoods, highways, and structures, directing attention, resources, and resilience where needed most,” Catbas concludes.
