Achievement
Abnormality detection of cable-stayed bridge
Project
IGERT: INTELLIGENT DIAGNOSTICS for Aging Civil Infrastructure
University
Northeastern University
(Boston, MA)
PI
Research Achievements
Abnormality detection of cable-stayed bridge
IGERT Fellow David Vines-Cavanaugh is working on abnormality detection of a cable-stayed bridge. The Zhanjiang Bay Bridge in South China was outfitted with a permanent Health Monitoring System (HMS) in December 2006. Zhanjiang Bay Bridge Co. Ltd. has provided David access to that data. From the results of a previously implemented abnormality detection strategy, it is suspected that the east end expansion joint is constraining the main girder's longitudinal motion by 10-20%. Using an alternative abnormality detection strategy, called a support vector machine (SVM), applied to the HSM data, David has shown reasonable results supporting the suspicion of the abnormality. David's conclusions are promising for SVM in its application to abnormality detection, and he is currently investigating potential limitations of the approach.
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