Numerical Verification on the Structural-health Evaluation of Subway Stations based on Statistical Pattern Recognition Technique

2012 
Subway is a representative public transportation that safety, above all, must be ensured. Therefore, subway stations need to be promptly maintained through the early detecting of damage conditions to guarantee the structural health and passengers` safety. However, it could be easily damaged by internal or external loads such as ambient train vibrations and even earthquake loads. For this reason, in this paper, authors suggest the structural-health evaluating algorithm based on the statistical pattern recognition techniques such as supervised and unsupervised learning method. And, also the numerical studies of Chungmuro station was carried out to verify the applicability of it into the structural-health evaluation of station structures.
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