Electromechanical Impedance Technique Research Articles

Numerical Analysis of Steel Frame Using Electro-Mechanical Impedance Technique

Nowadays, piezoelectric materials are most widely used in structural health monitoring (SHM) system for nondestructive evaluation. In this paper the damage study using electro-mechanical impedance (EMI) technique, which is nondestructive method of SHM. This paper presents a numerical analysis of four-story steel frame and multiple damages were induced in the steel frame by utilizing smart material like Lead Zirconate Titanate (PZT). A PZT-4 piezoelectric material was embedded in the beam of the frame. The type of damping used in steel frame model was Rayleigh damping. The numerical analysis was done in COMSOL MULTIPHYSICS 6.2 and frequency domain analysis was done, from that admittance values were find out for 30-300KHz frequency range. The real part of the admittance gives conductance values. Then, conductance verses frequency graph was created that will indicate the structural health and performance. Moreover, root mean square deviation (RMSD) index was found out for each case that provides a quantitative measure of deviation.

Assessing cement paste strength evolution under curing: An experimental and numerical investigation through equivalent stiffness parameter identified by embedded piezo sensors

Equivalent stiffness is one of the most important mechanical parameters of any concrete structure which allows engineers to predict the behaviour of the structure. This paper identifies the equivalent stiffness parameter through an embedded piezo sensor (EPS) in the strength development of cement paste using the electro-mechanical impedance (EMI) technique through experimental and numerical investigation. The experiments were conducted on the cement paste specimens; and the compressive strength (destructively) and EMI response were obtained during curing process. Further, a numerical model of cement paste specimen with EPS is developed to validate the EMI response. In addition, an equivalent stiffness parameter is identified from the experimental and simulation EMI data. It is found that the variation in conductance signature during curing process and strength development is effectively captured by the EPS. The identified equivalent stiffness either calculated from experimental or simulation data followed a similar behaviour of the compressive strength.

Corrosion monitoring for transmission line based on electromechanical impedance instrumented circular piezoelectric corrosion sensor

Corrosion-induced thickness loss is a common form structural damage in transmission lines. In our previous work, a novel circular piezoelectric-metal transducer for corrosion sensing using the electromechanical impedance (EMI) technique was proposed. This transducer was fabricated by attaching a lead zirconate titanate (PZT) patch to a metal plate. In the present study, the piezoelectric-metal transducer was encapsulated and enhanced, and two types of corrosion sensors were developed: piezoelectric-steel and piezoelectric-zinc sensors. To assess the practical performance of the corrosion sensors, the piezoelectric-steel and piezoelectric-zinc sensors were connected to the angle steels and the steel strands, which are highly prone to corrosion in transmission lines. Corrosion monitoring experiments were conducted in the laboratory. The results demonstrate that the peak frequencies in the conductance signatures decrease linearly with increasing corrosion-induced thickness loss. Furthermore, it was found that piezoelectric-steel sensors are effective for quantitative monitoring of metallic corrosion, whereas piezoelectric-zinc sensors are better suited for early-stage corrosion monitoring and warning.

Integrating the Capsule-like Smart Aggregate-Based EMI Technique with Deep Learning for Stress Assessment in Concrete.

This study presents a concrete stress monitoring method utilizing 1D CNN deep learning of raw electromechanical impedance (EMI) signals measured with a capsule-like smart aggregate (CSA) sensor. Firstly, the CSA-based EMI measurement technique is presented by depicting a prototype of the CSA sensor and a 2 degrees of freedom (2 DOFs) EMI model for the CSA sensor embedded in a concrete cylinder. Secondly, the 1D CNN deep regression model is designed to adapt raw EMI responses from the CSA sensor for estimating concrete stresses. Thirdly, a CSA-embedded cylindrical concrete structure is experimented with to acquire EMI responses under various compressive loading levels. Finally, the feasibility and robustness of the 1D CNN model are evaluated for noise-contaminated EMI data and untrained stress EMI cases.

Integrating PZT-based WP and EMI techniques with multi-criteria analysis for monitoring and assessment of mechanical properties of structural adhesives under curing

Structural adhesives are commonly employed as bonding agents in FRP strengthening systems. Measuring and assessing the mechanical properties of adhesives during the curing process is essential, as these properties directly influence the overall effectiveness of the strengthening system. This study investigated the development of mechanical properties in structural adhesives at various curing times using two PZT-based monitoring techniques, specifically wave propagation (WP) and electromechanical impedance (EMI) techniques. Two types of structural adhesives and two distinct curing temperatures (ambient temperature and mild temperature) were selected for examination. Throughout the adhesive curing process, both methods were utilized for monitoring. Subsequently, tensile tests were conducted to obtain the mechanical properties at different curing durations. The results demonstrate that monitoring indicators from both PZT-based techniques effectively captured the enhancement in adhesive performance during the curing process. Moreover, the tensile strength of the Sika and Carbon adhesives reached stability at ambient temperature after five and three days, respectively, while elevated temperatures accelerated the curing process. Furthermore, two Multi-Criteria Decision Making (MCDM) methods were employed to select monitoring indicators with the least deviation and the closest correlations with mechanical properties. These indicators have the potential to predict mechanical properties, potentially reducing the need for tensile tests.

Diagnosis and assessment of cyclic freeze–thaw damage in tunnel lining concrete using piezoelectric-based electromechanical impedance technique

Cold regional tunnel linings extensively suffer from severe cyclic freeze–thaw damage, which adversely influences their stability, durability and in-service safety. Consequently, the diagnosis and assessment of cyclic freeze–thaw damage in concrete linings have garnered worldwide attention. This study presents a pioneering effort in using the PZT-based electromechanical impedance (EMI) technique to monitor the evolving damage within lining concrete concurrently exposed to bending loads and freeze–thaw cycles. First of all, ultrasonic measurements and four-point bending tests were performed on cyclically freeze-thawed concrete specimens under two different bending loads. Both the degrading flexural strength and the diminishing ultrasonic wave velocity were measured. Particularly, the damage evolution was characterized by the flexural strength degradation ratio, which exponentially increased by 44.81% and 64.28% under two bending scenarios, respectively. Moreover, conductance signatures driven by two vibration modes (d31 and d33 modes) of embedded piezoelectric transducers were recorded, and both localized and overall variations in the signals were analyzed. It is concluded that both the resonant frequency shift and the statistic metric RMSD within the d31-dominated frequency range could accurately indicate the cyclic freeze–thaw damage of lining concrete. Their linear correlation coefficients with the damage variable reached 0.957 and 0.935, respectively. This research establishes a quantitative framework for monitoring the progressive damage of tunnel lining subjected to freeze–thaw cycling using the EMI technique and lays the groundwork for a broader range of future applications in structure damage diagnosis and assessment.

Identification of structural parameters in a prestressed concrete beam under chloride-induced corrosion using embedded and smart-probe-based piezo sensors

In prestressed concrete (PSC) structures, corrosion in prestressing wire is one of the main problems affecting its service life. Therefore, structural health monitoring (SHM) is essential for performance evaluation and safety maintenance to prevent and reduce engineering accidents. In SHM, corrosion monitoring using the piezo sensor-based electro-mechanical impedance (EMI) technique has become a research hotspot. This paper presents the effectiveness of embedded and smart-probe-based piezo sensors (SPPS) for identifying structural parameters such as stiffness, mass, and damping in a prestressed concrete beam subjected to chloride-induced corrosion using electro-mechanical impedance (EMI) technique. The accelerated corrosion tests were conducted on a PSC beam in which SPPS was indirectly bonded, and an embedded piezo sensor (EPS) was attached to the prestressing wire inside the beam to monitor the variation in the EMI signature during the exposure of corrosion. Further, a physical model was developed in the form of spring, mass, and damper combinations to identify the deterioration in terms of structural parameters during exposure to corrosion. Based on the experimental results, it is found that EPS is effective in identifying the corrosion initiation phase, while SPPS is for the corrosion propagation and cracking phase. In terms of percentage loss, the identified stiffness loss from SPPS and EPS in the propagation phase of corrosion is about 61.56 % and 5 %, respectively.

Monitoring of compressive strength gain in mass concrete using embedded piezoelectric transducers

AbstractThis study extended the electromechanical impedance (EMI) technique to monitor the 28‐day age of strength gain in mass concrete, although it has been validated in strength monitoring of a lab‐scaled concrete specimen. Embedded piezoelectric (PZT) transducer, namely, aluminum embedded PZT (AEP), that was wrapped by two sandwich aluminum pastes was proposed for EMI monitoring. The workability of the AEP was first verified via finite element analysis, where the effect of hydration heat on the EMI signature of the AEP was evaluated via numerical modeling and prior thermal test. In the experiment, totally four AEP transducers arranged at different loci were applied to monitor strength gain in a mass concrete specimen. As a comparison, the maturity method was also performed to estimate the strength of the specimen. Characteristics of EMI signature and its statistical indices including root mean square deviation (RMSD) and mean absolute percentage deviation (MAPD) were analyzed and correlated to strength development in mass concrete. Monitoring results indicated that the AEP transducers were capable of identifying the strength gain of mass concrete. The logarithmic function between the RMSD/MAPD index values and compressive strength perfectly predicted the strength development, which could be further employed for real‐life and in situ applications.

Effect of Different Weight on the Movable PZT Device on the Damage Detection Performance of Electromechanical Impedance Technique

This study presents a novel approach to conducting the electromechanical impedance (EMI) technique for delamination detection in composite structures without the need for permanently attaching PZT (Lead Zirconate Titanate) transducers to the surface. Instead, a device is created that can be simply placed on top of the composite structure, enabling one to perform the EMI technique for detecting damage. The primary objective is to investigate the effectiveness of this device in detecting delamination within composite materials. Additionally, this study explores the impact of placing additional weight on top of the transducer to investigate the performance of the device subjected to higher pressure. Experimental results and analysis will be presented to evaluate the feasibility and reliability of this approach for non-destructive testing and structural health monitoring of composite components. This research is significant as it lays the groundwork for developing automated damage detection systems using robotics in the near future. By demonstrating the proposed concept that can be easily integrated into robotic platforms, this study contributes to the advancement of automation in structural health monitoring. Implementing this technique in robotic systems has the potential to revolutionize maintenance practices by enabling continuous, real-time monitoring of composite structures, enhancing safety, and minimizing downtime due to structural defects. Moreover, the investigation into the impact of additional weight on the transducer’s performance is crucial for setting minimum weight limits in robotic systems, ensuring optimal functionality and accuracy during automated damage detection tasks.

An electromechanical impedance-based sensor for monitoring the pitting corrosion of steel: Simulation with experimental validation

Quantitative monitoring of steel corrosion plays a crucial role in evaluating structural safety and predicting structural performance. The electromechanical impedance (EMI) technique has already emerged for uniform corrosion monitoring. This study explores its potential for pitting corrosion monitoring. Specifically, two EMI-based sensor designs were proposed, namely the cylinder and the tube structures. Finite element models were developed to analyze the influence of the pit’s location, morphology parameters, as well as the random distribution of multiple pits, on the conductance peak frequency of sensors. The computer numerical controlled processes were employed to create random pits on sensors. Experimental results revealed that different distributions of pits correspond to distinct conductance peak frequencies, even with the same mass loss. Additionally, the tubular sensor exhibited reduced sensitivity to pits distribution compared to the cylindrical sensor. This is beneficial for accurately predicting mass loss induced by random pitting. This paper enhances the capability of EMI-based sensors for quantitatively monitoring pitting corrosion by focusing on structural design aspects.

Performance study of novel metal corrosion probes based on the adjust method of series and parallel connections

Rod-type metal corrosion probes based on electromechanical impedance (EMI) technique can quantitatively assess the amount of corrosion, which have a promising application in pipeline corrosion monitoring and have received much more attention. In the field of structural health monitoring, the EMI technique based on series and parallel connections has been widely studied and is very promising, but it is yet to be used in the probe design. In this work, a kind of novel metal corrosion probe with two piezoelectric elements in series and parallel connections was proposed, and its performance was investigated comprehensively by combining theoretical analysis with experiment research. Theoretical models of the proposed probe in the longitudinal vibration mode for both series and parallel connections were established, and verified by the experimental results. Influences of the thicknesses of piezoelectric layer and ceramic layer on the probe performance were analyzed. Artificial quantitative corrosion tests and accelerated corrosion tests were designed to evaluate the quantitative corrosion monitoring capacity. Temperature sensitivity tests were conducted to study the temperature dependence. The wireless impedance measurement was performed to confirm the online monitoring ability. Comparisons for the probe performance between the series and parallel connections were also presented. This work provided a comprehensive understanding for this kind of novel probe, which is beneficial to develop low-cost, high-precision, high-stability pipeline corrosion real-time monitoring technology.

Predicting concrete strength early age using a combination of machine learning and electromechanical impedance with nano-enhanced sensors

To ensure the structural integrity of concrete and prevent unanticipated fracturing, real-time monitoring of early-age concrete's strength development is essential, mainly through advanced techniques such as nano-enhanced sensors. The piezoelectric-based electro-mechanical impedance (EMI) method with nano-enhanced sensors is emerging as a practical solution for such monitoring requirements. This study presents a strength estimation method based on Non-Destructive Testing (NDT) Techniques and Long Short-Term Memory (LSTM) and artificial neural networks (ANNs) as hybrid (NDT-LSTMs-ANN), including several types of concrete strength-related agents. Input data includes water-to-cement rate, temperature, curing time, and maturity based on interior temperature, allowing experimentally monitoring the development of concrete strength from the early steps of hydration and casting to the last stages of hardening 28 days after the casting. The study investigated the impact of various factors on concrete strength development, utilizing a cutting-edge approach that combines traditional models with nano-enhanced piezoelectric sensors and NDT—LSTMs-ANN enhanced with nanotechnology. The results demonstrate that the hybrid provides highly accurate concrete strength estimation for construction safety and efficiency. Adopting the piezoelectric-based EMI technique with these advanced sensors offers a viable and effective monitoring solution, presenting a significant leap forward for the construction industry's structural health monitoring practices.

Automated estimation of early-age concrete compressive strength using EMI signature-driven deep learning technique

Concrete is a vital construction material for civil infrastructure, whose early-age compressive strength estimation plays a critical role in determining the proper time for formwork removal and the readiness of the structures for service. Electromechanical impedance (EMI) technique has been proven to be a non-destructive and effective method for monitoring concrete early strength gain. Nonetheless, such a technique heavily relies on effective frequency band selection and statistical parameter-based analysis, which may prevent the technique from a real-time operation. This study proposes an EMI signature-driven deep learning (DL) technique to enable the automated estimation of early-age concrete compressive strength. A novel DL framework called multi-scale learning residual denoising network (MLRD-Net) was developed to autonomously learn sensitive features from raw EMI signatures and ultimately estimate the compressive strength. The EMI signatures were collected during the strength development process of concrete specimens produced from two different mix designs based on strength. Two independent databases were constructed from recorded EMI signatures to test the effectiveness of the MLRD-Net. The results demonstrated the excellent performance of the proposed model with coefficients of determination exceeding 0.99 for both databases. In addition, the MLRD-Net showed superior performances over other methods in terms of prediction accuracy, noise resistance and fitness capacities, indicating its great potential for real-time and accurate estimation of the strength gain of early-age concrete.

EMI-based monitoring of prestressed concrete beam under chloride-induced corrosion using an embedded piezo sensor

The service life and durability of the prestressed concrete (PC) structures mainly depend on the corrosion resistance of the prestressing strands, wires, or tendons. Once corrosion occurs in the strands, identifying the location and quantifying the phases of corrosion is a very challenging task. Thus, this paper presents a novel way to monitor the corrosion process and identify the deterioration in a PC beam using an embedded piezo sensor (EPS) based on the electro-mechanical impedance (EMI) technique. The accelerated corrosion tests were conducted on a PC beam in which EPS was attached to the prestressing wire inside the beam to monitor the changes in the EMI signature during the corrosion progression. In addition, statistical damage indices such as root mean square deviation is identified to quantify the damage due to corrosion. Further, this study identifies the deterioration in mechanical changes such as stiffness, mass, and damping by extracting the equivalent structural parameters from the raw EMI signatures. Based on qualitative and quantitative results, it is found that the EPS effectively senses the changes at different time intervals during the corrosion process and identifies the damage of corrosion. Also, the equivalent stiffness parameter identified from raw EMI signatures is realistically measuring the material deterioration under corrosion and identifying the corrosion phases. Hence, it is concluded that the EMI technique based on EPS in structural health monitoring of PC beam can accurately assess the deterioration under the effect of corrosion.

Damage localization on reinforced concrete slab structure using electromechanical impedance technique and probability-weighted imaging algorithm

Damage localization plays a key role in structural damage identification and health monitoring. This paper proposed a new damage localization approach using electromechanical impedance/admittance (EMI/EMA) technique integrated with probability-weighted imaging algorithm based on Gaussian distribution. The proposed approach comprises five steps namely measurement of the EMA signature from an array of piezoelectric ceramic lead zirconate titanate (PZT) transducers, computation of statistic damage indicator, establishment of regression model for the indicator, damage visualization via Gaussian distribution and final damage localization. Experimental validation of the approach was conducted on a reinforced concrete (RC) slab with artificial crack damages detected by using an array of surface-bonded PZT patches. Comparative studies on localization accuracy were performed by utilizing root mean square deviation (RMSD), baseline-changeable RMSD namely RMSDk, mean absolute percentage deviation (MAPD) and correlation coefficient (CC). Experimental results demonstrated that the proposed approach could achieve precise localization of concrete crack with error as small as 0 mm, and that using RMSDk index exhibited the highest localization accuracy in average. The proposed approach promoted the capability of the EMI technique in characterization of concrete structural damages.

Development of piezoelectric impedance-based technique for rapid compressive strength measurement of mortar specimen using artificial neural network

Measurement of concrete strength is crucial for both the construction and maintenance stages of infrastructures. This importance is emphasized every year in Korea, where aging facilities require reliable and accurate assessment to prevent accidents. In general, three types of non-destructive testing methods are used for concrete maintenance, including the ultrasonic and rebound hardness methods, with a combination method also used. However, despite the popularity of these methods, there can be reliability issues as these methods estimate the strength of concrete through equations, rather than direct measurement. In this study, a non-destructive testing method known as the electromechanical impedance technique is used to predict the compressive strength of two different mortar specimens of 10 MPa and 30 MPa with the use of artificial neural network. In addition, the conventional method of permanently attaching the piezoelectric transducer was altered in a way to achieve temporary attachment to the host structure to make the proposed idea more useful for real field. The result from the experiments proves the possibility of predicting the difference in the compressive strength of the two mortar specimens.

Exploring chloride-induced corrosion in reinforced concrete structures through embedded piezo sensor technology: an experimental and numerical study

Corrosion of steel in concrete is one of the major problems with respect to the durability of reinforced concrete (RC) structures. Thus, monitoring the corrosion in real-time is essential to prevent structural damage. However, one of the main challenges is to simulate the real-time development of corrosion in the RC structure. In recent years, smart aggregates, also called embedded piezo sensors (EPS), have become increasingly popular for monitoring localized and corrosion damage in RC structures using electro-mechanical impedance (EMI). This paper presents the experimental and numerical investigation of corrosion in RC structures subjected to the chloride-laden environment using EPS via the EMI technique. To fulfil this objective, the study has been carried out in two stages such as; in the first stage, the experiments are conducted on the RC specimen, and the EMI response was obtained both in a pristine state and when accelerated corrosion progressed. In the second step, a numerical model of the RC specimen has been developed based on the experimental data in the COMSOL software, and the effect of corrosion in the form of varying mass loss percentages has been simulated. Based on the results, it is concluded that the experimental and numerical conductance signatures before and after corrosion are matched. The deterioration in terms of stiffness loss in the RC specimen was 18.20% at 30% mass loss.

Experimental and numerical investigation of the bonding conditions of piezoelectric sensors under high compressive strains on structures

In the past two decades, thin lead zirconate titanate (PZT) sensors have been widely used in the electro-mechanical impedance (EMI) technique for sensing applications, particularly for monitoring civil structures. They are typically surface bonded using an industrial adhesive to the monitored structure. The bond between a PZT sensor and structure must be sufficiently strong to transmit the response of the structure to the sensor. In this study, acrylic cubes bonded with PZT patches are subjected to high compressive strains above 2000 με to develop a better understanding of bonding conditions when structures undergo such high strains. Acrylic can undergo such high strains without developing fissures or cracks. Thus, the recorded EMI response only reflects changes in the bonding condition due to the development of strains. The experiments are also numerically supplemented by simulating various debonding conditions. At higher strains, it was observed that the admittance signatures tend to behave similarly to a freely vibrating PZT patch, indicating debonding around the periphery. Even after the complete unloading of the structure, the signatures did not return to their initial state, indicating a permanent partial debonding. The strains developed on a loaded structure are not uniform and can be localized due to structural imperfections, resulting in higher strains in the region where a sensor is bonded. The insights from this study will aid in expanding the scope of the application of PZT sensors for monitoring civil structures through better comprehension of the PZT-structure bond under high compressive strains.

Evaluation of Damage Severity and Strength of Structural Member Using Macro‐Molecular PZT Sensor

AbstractThe structural health of various engineering systems has been easily monitored using macromolecular piezoelectric ceramic lead zirconate titanate (PZT) based electromechanical impedance (EMI) technique. It is in need to study the evaluation of various levels of damage and the present strength of structural systems to enhance the life of structures. Once damages occur, due to continuing usage they usually propagate in certain directions. Moreover, the increase in the severity of damages may lead to failure of the structural components or even the whole structure. Interaction between structure and PZT, which is found effective in EMI technique, is to identify effective damage detection. The macro‐molecular PZT's self‐actuating and sensing properties are utilized by the electromechanical impedance (EMI) method. The higher modes of vibration are locally activated by the local application of an AC source on the PZT transducers attached to the host structure. In this paper, the EMI technique using surface‐bonded PZT transducers is employed to obtain the structural health signature. The experiment is carried out on a real‐size concrete frame structure subjected to artificial damage to identify and locate the damages using frequency variations, and the severity is checked using extracted equivalent parameters; the damage index. This method also can identify hair‐like cracks at an early stage, which explains how it can shield the building from serious failures.

Monitoring of crack repair in concrete using spherical smart aggregates based on electromechanical impedance (EMI) technique

Cracks will inevitably occur in concrete structures or members during the construction process and service life due to aging, environmental factors, external loads, etc. To improve the strength and stability of the cracked concrete structures, many methods have been proposed to repair the cracks. However, the monitoring of the repairing process and repair quality has not been fully studied. The previous studies have proved that the spherical smart aggregates (SSAs) based on the electromechanical impedance (EMI) technique have outperformed the traditional smart aggregates (SAs) based on the EMI technique in structural health monitoring of civil structures, however, SSAs have not been applied to the monitoring of the concrete crack repair. In this work, the monitoring of the concrete crack repair using the SSAs based on the EMI technique was explored. A total of eight concrete specimens were prepared, and cracks in the concrete specimens were simulated by manually cutting under laboratory conditions. According to the principle of grouting method, two repair agents including cement paste and cement mortar were used to repair the cracks. The impedance signals of 28 d were measured, and three quantitative indicators, namely root mean square deviation, mean absolute percentage deviation, and correlation coefficient deviation were used to evaluate the quality of the concrete repair effect. The results indicate that the SSAs show excellent sensitivity and stability over the traditional SAs. In addition, the normalized values of the quantitative indicators were analyzed to distinguish the types of repair agents. A mathematical expression of exponential function was also proposed by fitting the experimental data to quantitatively evaluate and predict the repair effect of concrete cracks. Further, the influences of temperature, humidity, crack depth and width on the experimental results were analyzed and discussed. The numerical simulation was also presented to validate the reasonability of the experimental results.