Identification of Simulated Damage in Prestressed Anchorage Using Admittance-Based Active Sensing Technique

This study examined the feasibility of the admittance-based method for detecting simulated damage in the bearing plate of a prestressed anchorage. The proposed method utilized the PZT (lead zirconate titanate) interface technique to acquire a strong admittance response from the anchorage. Firstly, the numerical feasibility of the method was demonstrated by detecting the presence of fatigue cracks and preload changes in a fixed-fixed beam-like structure. Next, the experimental verification was carried out using a lab-scale prestressed anchorage model. A PZT interface prototype was designed and surface-mounted on the bearing plate. The admittance response of the PZT interface was measured before and after the simulated damage cases of the bearing plate. Afterwards, a statistical damage metric, root-mean-square deviation (RMSD) was used to quantify the change in the admittance spectrum and identify the damage's presence. It was shown that the experimental admittance response was consistent with the numerical simulation result in the same effective frequency band. Both the numerical and experimental results showed clear shifts in the admittance spectrum due to structural damage. The simulated damages in the bearing plate were successfully identified by the RMSD evaluation metric.

Automated summary

This study explores the feasibility of using the admittance-based method to detect simulated damage in the bearing plate of a prestressed anchorage. The method was first numerically demonstrated to detect fatigue cracks and preload changes in a fixed-fixed beam-like structure. Then, experimental verification was conducted using a lab-scale prestressed anchorage model, and the presence of damage was identified through the change in the admittance spectrum measured before and after the simulated damage cases. The results showed consistent shifts in the admittance spectrum for both numerical and experimental scenarios, successfully identifying the simulated damages.