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Structural Control and Health Monitoring(2)
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Bayesian inference of dense structural response using vision-based measurements
ArticleAbstract: As-built structures typically behave differently than their analytical models because of uncertaintiPalabras claves:3D truss, Bayesian model updating, Computer Vision, Local measurements, Monte Carlo methods, Structural Health MonitoringAutores:Fernando Gómez Sánchez, Hoskere V., Narazaki Y., Smith M.D., Spencer B.F.Fuentes:googlescopusEfficient development of vision-based dense three-dimensional displacement measurement algorithms using physics-based graphics models
ArticleAbstract: This research investigates a framework for the efficient development of vision-based dense three-dimPalabras claves:Computer Vision, displacement measurement, physics-based graphics model, quantitative evaluation of algorithms, Structural Health MonitoringAutores:Fernando Gómez Sánchez, Hoskere V., Narazaki Y., Smith M.D., Spencer B.F.Fuentes:googlescopusSensor fault management techniques for wireless smart sensor networks in structural health monitoring
ArticleAbstract: Faulty sensor data often occur in structural health monitoring (SHM) systems using wireless smart sePalabras claves:distributed computing strategy, sensor fault management, Structural Health Monitoring, system identification, wireless sensor networkAutores:Fernando Gómez Sánchez, Fu Y., Narazaki Y., Peng C., Spencer B.F.Fuentes:googlescopusVisual–inertial displacement sensing using data fusion of vision-based displacement with acceleration
ArticleAbstract: In recognition of the importance of the displacement associated with assessing structural condition,Palabras claves:complementary filter, Computer Vision, displacement measurement, Sensor fusion, Structural Health MonitoringAutores:Fernando Gómez Sánchez, Kim J.R., Moon D.S., Park J.W., Spencer B.F., Yoon H.Fuentes:googlescopus