Vision-based stress estimation model for steel frame structures with rigid links

Hyo Seon Park, Jun Su Park, Byung Kwan Oh

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

This paper presents a stress estimation model for the safety evaluation of steel frame structures with rigid links using a vision-based monitoring system. In this model, the deformed shape of a structure under external loads is estimated via displacements measured by a motion capture system (MCS), which is a non-contact displacement measurement device. During the estimation of the deformed shape, the effective lengths of the rigid link ranges in the frame structure are identified. The radius of the curvature of the structural member to be monitored is calculated using the estimated deformed shape and is employed to estimate stress. Using MCS in the presented model, the safety of a structure can be assessed gauge-freely. In addition, because the stress is directly extracted from the radius of the curvature obtained from the measured deformed shape, information on the loadings and boundary conditions of the structure are not required. Furthermore, the model, which includes the identification of the effective lengths of the rigid links, can consider the influences of the stiffness of the connection and support on the deformation in the stress estimation. To verify the applicability of the presented model, static loading tests for a steel frame specimen were conducted. By comparing the stress estimated by the model with the measured stress, the validity of the model was confirmed.

Original languageEnglish
Article number075104
JournalMeasurement Science and Technology
Volume28
Issue number7
DOIs
Publication statusPublished - 2017 Jun 14

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science, ICT & Future Planning, MSIP) (No. 2011-0018360).

Publisher Copyright:
© 2017 IOP Publishing Ltd.

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Engineering (miscellaneous)
  • Applied Mathematics

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