Application of smart PZT sensors for damage assessment in concrete structures

Abstract

The objective of this study is to investigate the feasibility of an impedance-based damage detection technique using PZT (Lead-Zirconate-Titanate) patches for concrete structures. The impedance-based damage detection method is based on monitoring the changes in the electrical impedance. Those changes in the electrical impedance are due to the electro-mechanical coupling property of the PZT and the host structure. In this study, the PZT patches are bonded on the concrete surface for actuating and sensing the electromechanical impedance at the same time. This study is divided into two phases. In the first phase, two types of damages are assessed experimentally, of which one is the surface damage and the other is in-depth damage in plain concrete beam specimens. Progressive damage cases are simulated in the concrete specimens by making notches at regular intervals for both types of damages. Numerical simulation is done using commercial software ANSYS to check the validity of the experimental results. In the second phase of this study, realistic multiple damage scenario is created in a reinforced concrete beam by performing a third point bending test. The discrepancies in the electro-mechanical impedance signature are observed from sensors at different locations to assess damage and to predict the location of damage by applying progressive loading in a third point bending test. Emphasis is paid on checking the performance of the PZT sensors in a real damage situation and to detect the location of the multiple shear and flexural cracking by distributed sensors. Optimal frequency ranges according to thickness and lateral modes of the PZT sensors are selected for the efficient near and far field damage detection. The PZT electrical impedance signatures for intact state of the concrete specimens are compared with impedance signatures of different damage cases. In order to assess the different damage states, the shifts of resonant frequencies and root mean square deviat...