Effective damage identification is paramount to evaluating safety conditions and preventing catastrophic failures of concrete structures. Although various methods have been introduced in the literature, developing robust and reliable structural health monitoring (SHM) procedures remains an open research challenge. This study proposes a new approach utilizing a 1-D convolution neural network to identify the formation of cracks from the raw electromechanical impedance (EMI) signature of externally bonded piezoelectric lead zirconate titanate (PZT) transducers. Externally bonded PZT transducers were used to determine the EMI signature of fiber-reinforced concrete specimens subjected to monotonous and repeatable compression loading. A leave-one-specimen-out cross-validation scenario was adopted for the proposed SHM approach for a stricter and more realistic validation procedure. The experimental study and the obtained results clearly demonstrate the capacity of the introduced approach to provide autonomous and reliable damage identification in a PZT-enabled SHM system, with a mean accuracy of 95.24% and a standard deviation of 5.64%.

Effective real-time structural health monitoring in concrete structures is paramount to evaluating safety conditions and the timely maintenance of concrete structures. Especially, the presence of discrete fibers in fiber-reinforced concrete restrains crack propagation into small and thin cracks, which increases the difficulty in detecting damage. In this study, an array of piezoelectric lead zirconate titanate (PZT) transducers was applied to study the effects of external load-induced flexural stress and damage in fiber-reinforced concrete beams using the electromechanical impedance (EMI) or electromechanical admittance (EMA) methods. Beams were subjected to a four-point bending test under repeatable loading, while PZTs evaluated corresponding flexural stress and induced damage simultaneously. Due to the influence of the medium’s stress fields in the different types of wave propagation in structural elements, PZT transducers measurements are accordingly affected under variable stress fields, in addition to the effect of the higher level of damage that occurred in the medium. According to the results of the tests, variation in EMA signatures, following flexural stress and gradual damage changes, provided convincing evidence for predicting stress and damage development.

Traditional methods for estimating structural deterioration are generally costly and inefficient. Recent studies have demonstrated that implementing a network of piezoelectric transducers mounted to critical regions of concrete structural members substantially increases the efficacy of the structural health monitoring (SHM) method. This study uses a recently developed electro-mechanical-admittance (EMA)-based SHM system for real-time damage diagnosis of carbon FRP (C-FRP) ropes installed as shear composite reinforcement in RC deep beams. The applied SHM technique uses the frequency response measurements of a network of piezoelectric lead zirconate titanate (PZT) patches. The proposed strengthening methods using C-FRP ropes as ETS and NSM shear reinforcement and the applied anchorage techniques significantly enhanced the strength and the overall performance of the examined beams. The retrofitted beams exhibited increased shear capacity and improved post-peak response with substantial ductility compared with the brittle failure of the non-strengthened specimens. The health condition and the potential debonding failure of the applied composite fiber material were also examined and quantified using the proposed SHM technique. Damage quantification of C-FRP ropes is achieved by comparing and assessing the values of several statistical damage indices. The experimental results demonstrated that the proposed monitoring system successfully diagnosed the region where the damage occurred by providing early warning of the forthcoming critical shear cracking of concrete and C-FRP rope debonding failures. Furthermore, the internal PZT transducers showed sound indications of the C-FRP rope’s health condition, demonstrating a direct correlation with the mechanical performance of the fibers.

This experimental study investigates the influence of synthetic macro-fibers added in fiber-reinforced concrete (FRC) prismatic specimens on their flexural response and overall cracking performance. Application of a novel structural health monitoring (SHM) system that implements the electromechanical impedance (EMI) technique and the use of piezoelectric lead zirconate titanate (PZT) transducers installed in the FRC prisms are also included. The applied PZT-enabled EMI-based monitoring system was developed to diagnose damage and the overall performance in reinforced concrete (RC) structural members subjected to cyclic repeated loading, simulating seismic excitations in existing RC buildings. The paper also aims to determine the sensitivity of the real-time, wireless, and portable monitoring technique corresponding to the location, the distance, the direction of polarization of the PZT transducers and the location and magnitude of damage due to flexural cracking. Further, the influence of the effect of stresses corresponding at various loading levels and the observed changes in the ΕΜΙ frequency response of the PZT transducers are also examined. Test results indicated that cracking detection is achieved using this SHM system by prompt damage level assessment due to the FRC’s flexural load at early seismic loading stages in existing RC buildings.

Real-time structural health monitoring (SHM) and accurate diagnosis of imminent damage are critical to ensure the structural safety of conventional reinforced concrete (RC) and fiber-reinforced concrete (FRC) structures. Implementations of a piezoelectric lead zirconate titanate (PZT) sensor network in the critical areas of structural members can identify the damage level. This study uses a recently developed PZT-enabled Electro-Mechanical Impedance (EMI)-based, real-time, wireless, and portable SHM and damage detection system in prismatic specimens subjected to flexural repeated loading plain concrete (PC) and FRC. Furthermore, this research examined the efficacy of the proposed SHM methodology for FRC cracking identification of the specimens at various loading levels with different sensor layouts. Additionally, damage quantification using values of statistical damage indices is included. For this reason, the well-known conventional static metric of the Root Mean Square Deviation (RMSD) and the Mean Absolute Percentage Deviation (MAPD) were used and compared. This paper addresses a reliable monitoring experimental methodology in FRC to diagnose damage and predict the forthcoming flexural failure at early damage stages, such as at the onset of cracking. Test results indicated that damage assessment is successfully achieved using RMSD and MAPD indices of a strategically placed network of PZT sensors. Furthermore, the Upper Control Limit (UCL) index was adopted as a threshold for further sifting the scalar damage indices. Additionally, the proposed PZT-enable SHM method for prompt damage level is first established, providing the relationship between the voltage frequency response of the 32 PZT sensors and the crack propagation of the FRC prisms due to the step-by-step increased imposed load. In conclusion, damage diagnosis through continuous monitoring of PZTs responses of FRC due to flexural loading is a quantitative, reliable, and promising application.

Due to insufficient transverse reinforcement, the retrofitting of beam–column joints (BCJs) in existing reinforced concrete (RC) frame structures is commonly required to alter their brittle behavior. The construction industry has extensively embraced carbon-fiber-reinforced polymers (C-FRPs) as near-surface-mounted (NSM) reinforcement. Monitoring the performance of C-FRP retrofitting is crucial due to the wide range of factors influencing its effectiveness. A novel methodology has been implemented to assess the efficacy of the C-FRP retrofitting method in this study. This approach was validated through experimental investigation of full-scale BCJs, which were retrofitted with C-FRP ropes and subjected to cyclic loading. Furthermore, piezoelectric lead zirconate titanate (PZT) patches were placed on the NSM C-FRP ropes, and the electro-mechanical impedance (EMI) method was employed to monitor the retrofitting technique’s performance. A combination of the commonly used statistical damage index root mean squared deviation (RMSD) and a hierarchical clustering-based approach (HCA) was used to assess the performance of the C-FRP retrofitting technique. The experimental investigation results strongly indicate the proposed approach’s positive impact on the reliable assessment of C-FRP retrofitting performance. Thus, the proposed approach enhances the safety and resilience of retrofitted BCJs in RC structures.