detect crack
AI improves crack detection in nuclear reactors
As I write this, Futurama's Bender is on my TV expressing his opinions about the flaws of us humans. Although he may take it a little farther than I would, it's true that we don't have the best natural detection capabilities. And when you're talking about detecting structural flaws in something like a nuclear reactor, human error isn't something with which I'd want to take a chance. Luckily, technology is able to help us with this, and it's sure to be much more helpful than Bender the Robot. A system in development at Purdue University is poised to help operators detect cracks and their severity in nuclear reactors, according to a recent article by Chris Adam.
AI technology improves critical crack detection in nuclear reactors, bridges, buildings
A tiny crack in a nuclear reactor, skyscraper, bridge or dam can cause catastrophic consequences. The Minneapolis bridge collapse, which killed 13 people in 2007, is just one example of what can happen when structural integrity is compromised. Unidentified or under-identified structural damage in nuclear reactors can be cataclysmic. Inspection of critical systems such as nuclear reactors is complicated and time-consuming. Videos captured by an automatic crack detection system can easily misidentify small scratches or welds as cracks, so technicians must review videos frame by frame.
System uses 'deep learning' to detect cracks in nuclear reactors – RtoZ.Org – Latest Technology News
A system under development at Purdue University uses artificial intelligence to detect cracks captured in videos of nuclear reactors and represents a future inspection technology to help reduce accidents and maintenance costs. "Regular inspection of nuclear power plant components is important to guarantee safe operations," said Mohammad R. Jahanshahi, an assistant professor in Purdue's Lyles School of Civil Engineering. "However, current practice is time-consuming, tedious, and subjective and involves human technicians reviewing inspection videos to identify cracks on reactors." Complicating the inspection process is that nuclear reactors are submerged in water to maintain cooling. Consequently, direct manual inspection of a reactor's components is not feasible due to high temperatures and radiation hazards.
System uses 'deep learning' to detect cracks in nuclear reactors - Purdue University
WEST LAFAYETTE, Ind. – A system under development at Purdue University uses artificial intelligence to detect cracks captured in videos of nuclear reactors and represents a future inspection technology to help reduce accidents and maintenance costs. "Regular inspection of nuclear power plant components is important to guarantee safe operations," said Mohammad R. Jahanshahi, an assistant professor in Purdue's Lyles School of Civil Engineering. "However, current practice is time-consuming, tedious, and subjective and involves human technicians reviewing inspection videos to identify cracks on reactors." Complicating the inspection process is that nuclear reactors are submerged in water to maintain cooling. Consequently, direct manual inspection of a reactor's components is not feasible due to high temperatures and radiation hazards.
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