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Search Results - kimberly+cardillo
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AI method-apparatus for extracting crack-length from high-frequency AE signals
Reference #: 01536 The University of South Carolina is offering licensing opportunities for AI method-apparatus for extracting crack-length from high-frequency AE signals Background: In metallic structures, fatigue cracks are inevitable and need to be detected and quantified. However, the crack length information is hard to be estimated. It is imperative...
Published: 9/3/2022
|
Inventor(s):
Victor Giurgiutiu
,
Hanfei Mei
,
Joseph Garrett
,
Kimberly Cardillo
Keywords(s):
acoustic emission
,
artificial intelligence
,
crack length
,
fatigue crack growth
,
finite element simulation
,
machine learning
,
standing wave
,
structural health monitoring
Category(s):
Engineering and Physical Sciences