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Dynamic torsional response measurement model using motion capture system

  • Park, Hyo Seon (Department of Architectural Engineering, Yonsei University) ;
  • Kim, Doyoung (Department of Architectural Engineering, Yonsei University) ;
  • Lim, Su Ah (Department of Architectural Engineering, Yonsei University) ;
  • Oh, Byung Kwan (Center for Structural Health Care Technology in Building, Yonsei University)
  • Received : 2016.11.02
  • Accepted : 2017.05.07
  • Published : 2017.06.25

Abstract

The complexity, enlargement and irregularity of structures and multi-directional dynamic loads acting on the structures can lead to unexpected structural behavior, such as torsion. Continuous torsion of the structure causes unexpected changes in the structure's stress distribution, reduces the performance of the structural members, and shortens the structure's lifespan. Therefore, a method of monitoring the torsional behavior is required to ensure structural safety. Structural torsion typically occurs accompanied by displacement, but no model has yet been developed to measure this type of structural response. This research proposes a model for measuring dynamic torsional response of structure accompanied by displacement and for identifying the torsional modal parameter using vision-based displacement measurement equipment, a motion capture system (MCS). In the present model, dynamic torsional responses including pure rotation and translation displacements are measured and used to calculate the torsional angle and displacements. To apply the proposed model, vibration tests for a shear-type structure were performed. The torsional responses were obtained from measured dynamic displacements. The torsional angle and displacements obtained by the proposed model using MCS were compared with the torsional response measured using laser displacement sensors (LDSs), which have been widely used for displacement measurement. In addition, torsional modal parameters were obtained using the dynamic torsional angle and displacements obtained from the tests.

Keywords

Acknowledgement

Supported by : National Research Foundation of Korea (NRF)

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