Workplace safety is a big deal, particularly in industries such as construction, where equipment failures can lead to serious injuries.
Engineering researchers at Penn State University are looking to combat the numerous fatalities in the construction industry, many related to falls, by incorporating cyber-physical systems (CPS) into the temporary equipment and structures used during building and construction projects.
CPS are engineered systems that are built from integration between computational algorithms and physical sensor components. With an array of these sensors installed on all equipment, the sensor information from across a worksite can be fed into a central computer.
This computer system will constantly monitor the equipment’s structural integrity, and report any issues to people on the jobsite, warning of possible failures and preventing potential accidents.
The study is being conducted by Xiao Yuan, an architectural engineering Ph.D. candidate at the Penn State College of Engineering. By investigating how to link the sensors on the structures and virtual models, Yuan hopes to identify equipment failures and weaknesses before they become serious problems.
“Once there is a problem, our virtual model will know,” Yuan said. “It’s just like when we feel something if it hurts – the virtual model will feel if there is a problem.”
If a problem is identified by the sensors, it will be highlighted on the virtual 3D model, and will send notifications to the workers on-site, as well as inspectors and project managers. With this information at hand, professionals on-site can assess and repair any damage to the equipment.
So far, Yuan has tested a number of different failure scenarios in a lab setting, from an overloaded scaffold moving in the wind to an improperly connected or missing scaffolding brace.
The biggest boon to come out of this research, however, may be to the development of “intelligent” systems that will learn and interpret information in the virtual model to better assess problems in the future.
However, getting such a system in place is still the next step.
“The virtual model can learn from historical behavior for intelligent identification of potential hazards in the future,” said Yuan. “There are some limitations to testing the system in the labs. If we want to apply this technology in the real world, we need to test in the real world.”
To find out more, visit the Penn State College of Engineering website.
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