Paper
9 March 2014 Numerical analysis of PZT rebar active sensing system for structural health monitoring of RC structure
F. Wu, J. Yi, W. J. Li
Author Affiliations +
Abstract
An active sensing diagnostic system for reinforced concrete SHM has been under investigation. Test results show that the system can detect the damage of the structure. To fundamentally understand the damage algorithm and therefore to establish a robust diagnostic method, accurate Finite Element Analysis (FEA) for the system becomes essential. For the system, a rebar with surface bonded PZT under a transient wave load was simulated and analyzed using commercial FEA software. A detailed 2D axi-symmetric model for a rebar attaching PZT was first established. The model simulates the rebar with wedges, an epoxy adhesive layer, as well as a PZT layer. PZT material parameter transformation with high order tensors was discussed due to the format differences between IEEE Standard and ANSYS. The selection of material properties such as Raleigh damping coefficients was discussed. The direct coupled-field analysis type was selected during simulation. The results from simulation matched well with the experimental data. Further simulation for debonding damage detection for concrete beam with the PZT rebar has been performed. And the numerical results have been validated with test results too. The good consistency between two proves that the numerical models were reasonably accurate. Further system optimization has been performed based on these models. By changing PZT layout and size, the output signals could be increased with magnitudes. And the damage detection signals have been found to be increased exponentially with the debonding size of the rebar.
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F. Wu, J. Yi, and W. J. Li "Numerical analysis of PZT rebar active sensing system for structural health monitoring of RC structure", Proc. SPIE 9063, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2014, 906314 (9 March 2014); https://doi.org/10.1117/12.2045560
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Cited by 2 scholarly publications.
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KEYWORDS
Ferroelectric materials

Active remote sensing

Sensing systems

Structural health monitoring

Finite element methods

Numerical analysis

Damage detection

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