Research Article
A Proposal of the Gage-Free Safety Assessment Technique for the Steel Beam Structure Under Uncertain Loads and Support Conditions Using Motion Capture System
@INPROCEEDINGS{10.1007/978-3-319-13329-4_19, author={Jun Park and Byung Oh and Se Choi and Tongjun Cho and Yousok Kim and Hyo Park}, title={A Proposal of the Gage-Free Safety Assessment Technique for the Steel Beam Structure Under Uncertain Loads and Support Conditions Using Motion Capture System}, proceedings={Ad Hoc Networks. 6th International ICST Conference, ADHOCNETS 2014, Rhodes, Greece, August 18-19, 2014, Revised Selected Papers}, proceedings_a={ADHOCNETS}, year={2014}, month={11}, keywords={Structural health monitoring Strain estimation Structural safety steel beam Maximum stress Vision based monitoring Motion capture}, doi={10.1007/978-3-319-13329-4_19} }- Jun Park
Byung Oh
Se Choi
Tongjun Cho
Yousok Kim
Hyo Park
Year: 2014
A Proposal of the Gage-Free Safety Assessment Technique for the Steel Beam Structure Under Uncertain Loads and Support Conditions Using Motion Capture System
ADHOCNETS
Springer
DOI: 10.1007/978-3-319-13329-4_19
Abstract
Estimating the maximum stress through stress distribution of a structure is an important indicator for structural safety evaluation. Structural health monitoring can be used to do this with a variety of measuring equipment such as strain gage, LVDT, LDS. All the measuring equipment, however, has some weakness in the configuration of complex wire network and some inconvenience of replacing faulty sensors. Therefore, this paper suggests a technique that can estimate stress distribution of steel beam structure under uncertain load and support conditions by using motion capture system (MCS). MCS is a Vision-based Monitoring System, which measures 3D coordinates of multiple markers attached to the surface of steel beam without installing the complex wire network. In this study, the stress distribution is estimated from an analytic model by using displacement values measured by MCS. For the evaluation of the estimated stress distribution, comparing with the measured stress from ESG is performed.
