Electromechanical Impedance Research Articles

Research on the influence of an adhesive layer on the monitoring signal of piezoelectric sensors

Electromechanical impedance (EMI) technology, as one of the important methods for analyzing and studying the interaction between sensors and structures, has the characteristics of clear physical meaning and high computational efficiency. However, for complex structures, it is difficult to quantitatively combine the measured impedance signal with the physical parameters of the tested structure. Therefore, establishing an appropriate EMI model is crucial to facilitate the quantitative analysis of structural health monitoring. The impedance models developed so far assume perfect adhesion between PZT and the structure, with displacement compatibility, and ignore the shear lag effect of the adhesive layer. Therefore, this research focuses on analyzing how surface-bonded PZT couples with the structure through the adhesives and conducting a shear layer analysis on two-dimensional (2-D) circular PZT to derive a closed-form solution for shear lag distribution. The shear lag effect is integrated into the 2D impedance formula. The influence of the adhesive layer on bolt loosening monitoring is studied, and it is proven that the modified EMI model can effectively predict the shear lag effect of the adhesive layer. The result of relative error analysis proves that conventional adhesive PZT also exhibits the shear lag phenomenon. The influence of different thicknesses of adhesive layers on sensor sensitivity is studied. The experimental results show that as the thickness of the adhesive layer decreases, the monitoring sensitivity of the sensor increases. Moreover, for slight bolt loosening, the thickness of the adhesive layer can affect the monitoring frequency.

Thermal Hysteresis Effect and Its Compensation on Electro-Mechanical Impedance Monitoring of Concrete Structure Embedded with Piezoelectric Sensor

Piezoelectric (PZT) sensors employed in the electro-mechanical impedance/admittance (EMI/EMA) technique are vulnerable to temperature variations when applied to concrete structural health monitoring (SHM). However, in practice, the ambient temperature transmitted from the air or surface to the concrete inner part is time-dependent during its monitoring process, which inflicts a critical challenge to ensure accurate signal processing for PZT sensors embedded inside the concrete. This paper numerically and experimentally investigated the thermal hysteresis effect on EMA-based concrete structure monitoring via an embedded PZT sensor. In the numerical modeling, a 3D finite element model of a concrete cube embedded with a PZT sensor was generated, where thermal hysteresis in the concrete, adhesive coat, and sensor was fully incorporated by introducing a temperature gradient. In the experiment, an equal-sized concrete cube installed with a cement-embedded PZT (CEP) sensor was cast and heated for 180 min at four temperature regimes for EMA monitoring. Experimental results, as a cogent validation of the simulation, indicated that EMA characteristics were functionally correlated to the dual effect of both heat transfer and the temperature regime. Moreover, a new approach relying on the frequency/magnitude of the maximum resonance peak in the EMA spectrum was proposed to effectively compensate for the thermal hysteresis effect, which could be regarded as a promising alternative for future applications.

Curing process monitoring of polymeric composites with Gramian angular field and transfer learning-boosted convolutional neural networks

Continuous and accurate monitoring of the degree of curing (DoC) is essential for ensuring the structural integrity of fabricated composites during service. Although machine learning (ML) has shown effectiveness in DoC monitoring, its generalization and extendibility are limited when applied to other curing-related scenarios not included in the previous learning process. To break through this bottleneck, we propose a novel DoC monitoring approach that utilizes transfer learning (TL)-boosted convolutional neural networks alongside Gramian angular field-based imaging processing. The effectiveness of the proposed approach is validated through experiments on metal/polymeric composite co-bonded structures and carbon fiber reinforced polymers using raw sensor data separately collected through the electromechanical impedance and fiber Bragg grating (FBG) measurements. Four indicators, accuracy, precision, recall, and F1-score are introduced to evaluate the performance of generalization and extendibility of the proposed approach. The indicator scores of the proposed approach exceed 0.9900 and outperform other conventional ML algorithms on the FBG dataset of the target domain, demonstrating the effectiveness of the proposed approach in reusing the pre-trained base model on the composite curing monitoring issues.

Evaluation of boundary and material influences on the dynamic electromechanical impedance response of the embedded PZT sensor in concrete

Evaluation of boundary and material influences on the dynamic electromechanical impedance response of the embedded PZT sensor in concrete

A novel approach to alloy-based bonding for piezoelectric sensor integrated in impedance-based structural health monitoring

ABSTRACT Structural health monitoring aided with the electromechanical impedance technique (EMI) is gaining popularity among researchers due to its dual sensing application and noise-free sensor results, and it is very sensitive to inceptive structural alternation. A thin coat of adhesive permanently bonds the piezoelectric transducers to the host structure. The bonding layers effect the mechanical interaction between the structure and the piezoelectric material as they act as a pure shear connector. Furthermore, the presence of shear alters the actuation and sensing capability of the PZT (Piezoelectric Transducer) patch, hence the efficiency of EMI technique. In this paper, a novel alloy (Sn-Ag) based bond is introduced for sensor integration and studied for bond behaviour in order to improve the bond’s quality in the EMI approach for structural health monitoring. The first part of experiment deals bond geometry degradation deals with the effect of disbond towards impedance-based coupled signature. The last part of experiment focuses on bond exposure to environmental degradation and it’s durability. From the experimental results, it is found that the Sn-Ag alloy-based bond formed between the structure and the piezoelectric transducer with the help of thermos-activated process is extremely strong and establishes a unique bond layer connection to the structure, which has a more resistive capacity towards moisture, chemical, and also temperature, compared with the epoxy-based bond.

Damage Metrics for Void Detection in Adhesive Single-Lap Joints

Structural Health Monitoring (SHM) techniques, such as Electromechanical Impedance Spectroscopy (EMIS), aim to continuously monitor structures for defects, thus avoiding the need for regular maintenance. While attention has been given to the application of EMIS in the automatic detection of damage in metallic and composite components, integrity monitoring of structural adhesive joints has been comparatively neglected. This paper investigated the use of damage metrics with electrical impedance measurements to detect defects in Single-Lap Joints (SLJs) bonded with a modified epoxy adhesive. Traditional metrics using statistical and distance-based concepts, such as the Root-Mean-Squared Deviation, RMSD, or the Correlation Coefficient, CC, are addressed at detecting voids in the adhesive layer and are applied to five different spectral frequency ranges. Furthermore, new damage metrics have been developed, such as the Average Canberra Distance, ACD, which enables a reduction of possible outliers in damage detection, or the complex Root-Mean-Squared Deviation, cRMSD, which allows for the use of both the real and imaginary components of the impedance, enabling better damage detection in structural adhesive joints. Overall, damage detection is achieved, and for certain spectral conditions, differentiation between certain damage sizes, using specific metrics, such as the RMSD or cRMSD, may be possible. Overall, the RMSD or cRMSD values from damaged SLJs tend to be double the metric values from undamaged joints.

Nondestructive Testing and Health Monitoring Techniques for Structural Effective Prestress

Prestressed structures are widely employed in bridges and large-span spatial structures, and the accurate evaluation of prestress state is of great importance for structural maintenance. This paper reviews the nondestructive testing (NDT) and health monitoring techniques for structural effective prestress. Specifically, the fiber Bragg grating (FBG) sensor-based, magnetic-elastic (ME) sensor-based, dynamic response-based, ultrasonic guided wave (UGW)-based, electromechanical impedance (EMI)-based, and electrical resistance-based methods are reviewed in this paper. Firstly, the principle, application range, and measuring accuracy of each technique are introduced and analyzed, and the benefits and limitations of each technique are summarized: The FBG sensor and ME sensor take on high measuring accuracy and have been applied in practical engineering, but they are required to be preinstalled during structural construction; the dynamic response-based method is greatly effective in cable force assessment but not suitable for prestress evaluation of prestressed concrete (PSC) structures; the UGW-based, EMI-based, and electrical resistance-based methods have shown favorable potential for prestress assessment in laboratory experiments, but their feasibility and accuracy in practical engineering need to be verified. Secondly, the challenges and discussion of each method are discussed in the following four aspects: measuring range, reliability of measuring results, stability and durability considering long-term monitoring, and cost-efficiency. Finally, a decision tree is proposed to choose the most appropriate prestress evaluation method in a specific application scenario.

Structural Health Monitoring of Fiber-Reinforced Concrete Prisms with Polyolefin Macro-Fibers Using a Piezoelectric Materials Network under Various Load-Induced Stress

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.

Damage detection and localization based on different types of actuators using the electromechanical impedance method in 3D-printed material

Electromechanical impedance (EMI) measurement, using piezoelectric transducers (PZTs) in the high-frequency range is a potential method for assessing the health of lightweight structures. The major objective of this work is to comprehend how different actuators react to damage in additively manufactured (AM) polymer structures. A novel frequency-range selection technique was suggested based on the maxima of the standard deviation of the impedance frequency spectra gathered for the referential and damage cases. A 3D-printed acrylonitrile butadiene styrene (ABS) plate was used for the investigation, where two PZT and one macro fiber composite (MFC) actuator were glued to the surface. Small magnets were used to simulate damage and were positioned at increasing distances from each transducer as EMI measurements were made using the MFC and 1 PZT. This served both in studying the transducers’ sensitivity to damage and selecting the proper frequency range for damage detection utilizing the standard-deviation approach. The EMI-acquired data from the MFC actuator displays damage-sensitive peaks in a low-frequency band (0–58 ), while the PZT shows a good sensitivity in a higher frequency range (94–304 ). In order to evaluate the PZT and MFC actuators’ sensitivity to damage in the 3D-printed ABS plate, impact damage is also generated in the plate’s center. The impedance-based damage indices obtained from different types of PZTs (2 PZTs and 1 MFC) were projected to the same base level and then fused—for the first time—for impact-damage localization and further added magnetic mass damage localization. The obtained damage index values of impedance are encouraging for the evaluation of AM polymer structures with a 4.48 mm positional error from a real location by fusing data in the different frequency ranges for PZTs and MFC. The damage localization error increases significantly to the new location beyond the damage sensitivity range of the PZT2 and MFC for the added magnetic mass on the 3D printed structure.

A Review of Approaches for Mitigating Effects from Variable Operational Environments on Piezoelectric Transducers for Long-Term Structural Health Monitoring.

Extending the service life of ageing infrastructure, transportation structures, and processing and manufacturing plants in an era of limited resources has spurred extensive research and development in structural health monitoring systems and their integration. Even though piezoelectric transducers are not the only sensor technology for SHM, they are widely used for data acquisition from, e.g., wave-based or vibrational non-destructive test methods such as ultrasonic guided waves, acoustic emission, electromechanical impedance, vibration monitoring or modal analysis, but also provide electric power via local energy harvesting for equipment operation. Operational environments include mechanical loads, e.g., stress induced deformations and vibrations, but also stochastic events, such as impact of foreign objects, temperature and humidity changes (e.g., daily and seasonal or process-dependent), and electromagnetic interference. All operator actions, correct or erroneous, as well as unintentional interference by unauthorized people, vandalism, or even cyber-attacks, may affect the performance of the transducers. In nuclear power plants, as well as in aerospace, structures and health monitoring systems are exposed to high-energy electromagnetic or particle radiation or (micro-)meteorite impact. Even if environmental effects are not detrimental for the transducers, they may induce large amounts of non-relevant signals, i.e., coming from sources not related to changes in structural integrity. Selected issues discussed comprise the durability of piezoelectric transducers, and of their coupling and mounting, but also detection and elimination of non-relevant signals and signal de-noising. For long-term service, developing concepts for maintenance and repair, or designing robust or redundant SHM systems, are of importance for the reliable long-term operation of transducers for structural health monitoring.

Electro-mechanical impedance technique for concrete strength monitoring: Three-dimensional model development and experimental verification

During the application of the electro-mechanical impedance (EMI) technique for detecting the strength development of concrete, in some cases, the piezoelectric sensor is embedded in the concrete. Normally, there are two methods to embed the piezoelectric sensor: PS-EMI and CPS-EMI. For both methods, the observed resonance frequency of the piezoelectric sensor increases with the increase of the concrete strength. However, there is a contradiction in the trend of conductance amplitude at the resonance frequency, which has to an extent puzzled the researchers in this area. In this paper, we developed a three-dimensional EMI model for the embedded piezoelectric sensor. We discussed the underlying mechanism, which induces the conductance spectrum difference for the PS-EMI and CPS-EMI, and experimental verification was carried out. By plotting the evolution of the concrete strength as a function of the resonance frequency shift, it was found that both embedding methods can be used in practical applications.

Real Time Assessment of Smart Concrete Inspection with Piezoelectric Sensors

Utilization of an Electromechanical impedance (EMI) technique with Piezoelectric (PZT) sensors has showed potential for Structural Health Monitoring (SHM). The changes in mechanical structure via flexural bending and cracking can be detected by monitoring the deviations in electrical impedance signals recorded with embedded PZT sensors. This paper has conducted a comprehensive study on the potential of an EMI technique with embedded PZT sensors with 3D Concrete Printing (3DCP) structures subjected to flexural bending test until plastic failure. The impact of different Piezoelectric housing methods and materials has been studied comprehensively through the monitoring of EMI signals. Experimental results indicate that material housing types and thickness affect the sensitivity of EMI readings but also performed as a reinforcement when a load is directly applied. The embedded PZT sensors with the EMI technique have shown strong potential to address the cost and lifecycle challenges posed by traditional construction methods as the insertion of PZT sensors seamlessly functions with 3DCP workflows. Further developmental work can be carried out to address the sensitivity of the sensor, performance as a reinforcement, and installation automation. The results proved that the coated sensors could detect fractures in 3DCP concrete with decreased sensitivity on thicker coating layers through the variance in materials and coating thickness in the paper.

Parametric analysis of RSB sensors for concrete strength monitoring using hybrid EMI and WP techniques: Numerical investigation

The strength of concrete after its casting increases with time up to a certain limit due to continuous hydration reactions in the cement matrix. To measure the rate of strength development and ultimate capacity of concrete, a novel health monitoring method using Reusable smart bolt (RSB) piezoelectric sensor is proposed in the present paper. The smart piezoelectric Lead zirconate titanate (PZT) patch-based Electro-mechanical impedance (EMI) and Wave propagation (WP) techniques are utilised for accessing the health of concrete at 1, 3, 5, 7, 14, 21 & 28 days of concrete hydration. Firstly, the PZT patch-based sensing capabilities are validated with the experimental results from literature by modelling concrete cube for EMI and beam for WP results. Then, a total of 31 finite element models of concrete cubes having different RSB configurations were taken into consideration for sensor design and optimization. In EMI technique, the shifting of conductance signatures and relative resonance frequency are measured, whereas in WP technique, the shift of P-wave velocity peaks between actuator and sensor is estimated for all the models. The sensitivity of outputs is measured by plotting statistical Root mean square deviation (RMSD) index which proven the efficacy of employing RSB sensors for monitoring concrete strength-development during early-hydration ages with good correlations. Overall, the EMI-identified RMSD plotted for conductance shows 327 % more sensitivity than WP-identified relative change of P-wave velocity in monitoring concrete strength development using RSB sensors.

Evaluation of Setting Times of Concrete Using Electro-Mechanical Impedance Sensing Technique.

This study presents a novel approach to assessing the setting time of concrete using the electro-mechanical impedance (EMI) sensing technique. The proposed method involves the continuous monitoring of EMI changes by embedding a piezoelectric (PZT) sensor directly in the concrete. A comparative analysis was conducted with the conventional penetration resistance test, which utilizes mortar samples extracted from the concrete. As a result of the experiment, the time deviation rate of the setting time was more than 10% in the penetration resistance test using the mortar sample extracted from the same concrete, whereas the time deviation rate of the setting time was up to 1.77% in the EMI sensing technique using the same concrete specimen. This highlights the effectiveness and potential of the EMI sensing technique for an improved evaluation of concrete setting time.

Piezoelectric Wafer Active Sensor Transducers for Acoustic Emission Applications.

Piezoelectric materials are defined by their ability to display a charge across their surface in response to mechanical strain, making them great for use in sensing applications. Such applications include pressure sensors, medical devices, energy harvesting and structural health monitoring (SHM). SHM describes the process of using a systematic approach to identify damage in engineering infrastructure. A method of SHM that uses piezoelectric wafers connected directly to the structure has become increasingly popular. An investigation of a novel pitch-catch method of determining instrumentation quality of piezoelectric wafer active sensors (PWASs) used in SHM was conducted as well as an investigation into the effects of defects in piezoelectric sensors and sensor bonding on the sensor response. This pitch-catch method was able to verify defect-less instrumentation quality of pristinely bonded PWASs. Additionally, the pitch-catch method was compared with the electromechanical impedance method in determining defects in piezoelectric sensor instrumentation. Using the pitch-catch method, it was found that defective instrumentation resulted in decreasing amplitude of received and transmitted signals as well as changes in the frequency spectrums of the signals, such as the elimination of high frequency peaks in those with defects in the bonding layer and an increased amplitude of around 600 kHz for a broken PWAS. The electromechanical impedance method concluded that bonding layer defects increase the primary frequency peak's amplitude and cause a downward frequency shift in both the primary and secondary frequency peaks in the impedance spectrum, while a broken sensor has the primary peak amplitude reduced while shifting upward and nearly eliminating the secondary peak.

Impact energy assessment of sandwich composites using an ensemble approach boosted by deep learning and electromechanical impedance

Sandwich composites are prone to delamination and fracture during service when exposed to external low-velocity impact. One hindrance to overcome before a broader deployment of sandwich composites is the issue of impact energy assessment (IEA). To promote the solution to this issue, an ensemble deep learning approach is proposed in this study. The approach comprises data expansion, series-to-image conversion, and convolutional neural networks (CNN). The data expansion is implemented using vertical average interpolation. The enhanced data are transformed into images via the Gramian angular summation field to build an image dataset for the CNN model. To validate the developed ensemble approach, hammer-dropping impact experiments on the honeycomb sandwich composites are carried out based on the piezoelectric wafer active sensor network and electromechanical impedance measurement. Accuracy, precision, recall, and F1-score indicators are introduced to evaluate the ensemble approach performance. The above indicator values are all above 0.9600, demonstrating the effectiveness of the proposed ensemble approach in settling the IEA issue.

Electro-Mechanical Impedance-Based Structural Health Monitoring of Fiber-Reinforced Concrete Specimens under Four-Point Repeated Loading

Fiber Reinforced Concrete (FRC) has shown significant promise in enhancing the safety and reliability of civil infrastructures. Structural Health Monitoring (SHM) has recently become essential due to the increasing demand for the safety and sustainability of civil infrastructures. Thus, SHM provides critical benefits for future research to develop more advanced monitoring systems that effectively detect and diagnose the damage in FRC structures. This study investigates the potential of an Electro-Mechanical Impedance (EMI) based SHM system for detecting cracks in FRC prisms subjected to four-point repeated loading. For the needs of this research, an experimental investigation of three FRC specimens with the dimensions 150 × 150 × 450 (mm) were subjected to three different loading levels where no visual cracks formed on their surface. Next, prisms were subjected to reloading until they depleted their load-carrying capacity, resulting in pure bending fracture at the mid-span. A network of nine cement paste coated Piezoelectric lead Zirconate Titanate (PZT) transducers have been epoxy bonded to the surface of the FRC prisms, and their frequency signal measurements were utilized for quantitative damage assessment. The observed changes in the frequency response of each PZT sensor are evaluated as solid indications of potential damage presence, and the increasing trend connotes the severity of the damage. The well-known conventional static metric of the Root Mean Square Deviation (RMSD) was successfully used to quantify and evaluate the cracking in FRC specimens while improving the efficiency and accuracy of damage detection. Similarly, the dynamic metric of a new statistical index called “moving Root Mean Square Deviation” (mRMSD) was satisfactorily used and compared to achieve and enhance accuracy in the damage evaluation process.

Monitoring of the curing process and thermal failure of adhesive-bonded structures based on damping measurement using quantitative electromechanical impedance

Adhesives are essential materials in engineering and their strength directly affects the safety of structures. The curing and environmental deterioration are critical areas of focus in adhesive researches. However, conventional studies on adhesive curing emphasize only on the characteristics of the adhesive itself, while studies on deterioration of adhesive-bonded structure tend to concentrate on detecting disbonds. In this work, we proposed to monitor the curing process and thermal failure of adhesive-bonded-structures based on damping measurement using a quantitative electromechanical impedance (Q-EMI) method. The performances of two adhesives, i.e. epoxy and cyanoacrylate, were studied via bonding a piezoelectric transducer onto one end of an alumina bar and measuring the admittance spectrum of the transducer-adhesive-alumina system. Results show that the damping steadily decreases during the curing process and eventually stabilizes for both adhesive-bonded structures. A significantly higher curing rate is observed at 60 °C compared to that at room temperature. At high temperatures, the damping will increase dramatically, or no peaks can be observed in the admittance spectrum, indicating adhesive failure. The results indicate that the epoxy adhesive can function normally at temperatures up to 120 °C and can endure heating-cooling cycles up to 180 °C, while the cyanoacrylate adhesive can function normally at 140 °C but fails upon cooling. The proposed Q-EMI method is quite powerful in monitoring the performances of bonded structures.

Research on bolt looseness monitoring based on electromechanical impedance transmissibility technology

Centralized damage, such as bolt looseness, is one of the most common types of damage in bridge structures. Thus, early detection of such damage is essential for bridge maintenance. Detection methods based on transmittance functions (TFs) have been widely studied. These functions use a T matrix to calculate damage indicators and reflect changes in dynamic parameters, such as natural structural frequencies. However, existing research has shown that the excitation position significantly impacts the T matrix. Therefore, this study proposes a new method based on electromechanical impedance (EMI) for local damage characterization, namely, EMI-TF. A series of comparative tests shows that the EMI-TF process is more sensitive and accurate than the traditional TFs. In addition, the sensitivity of the EMI-TF and EMI methods is compared. Results show that using EMI-TF technology can achieve the localization of minor damage at lower frequencies, which, to some extent, overcomes the limitations of the traditional EMI method that can only detect minor damage at high frequencies. The repeatability of EMI-TF is also studied separately in experiments, with ten repeated experiments conducted. Results show that the experimental results of EMI-TF have high repeatability.

Performance evaluation concept for crack healing in bacterial concrete structure using electro mechanical impedance technique with PZT patch

Beginning and development of cracks reduce the structural performance and durability, thus a novel strategy is required to prevent such kind of occurrence. The incorporation of bacteria in the concrete system is likewise a technique to prevent the growth of the cracks by the microbial induced calcite precipitation. The Electro mechanical impedance (EMI) technique is the smart sensor-based technology that is an efficacious technique to examine the health of structures, whereas the prediction of frequency band and corresponding healing damage indicator for real-life application is the governing factor. The examination of crack healing performance in bacterial concrete by EMI technique with PZT sensors was not reported by previous studies to date. This research is motivated by the quality evaluation of crack healing in bacterial reinforced concrete beam specimens using the EMI technique with surface-bonded PZT patch and embedded concrete vibration sensor (CVS), respectively. For the fabrication of bacterial reinforced concrete beam specimen, the Gram-positive Bacillus subtilis bacteria have been used. To induce the structural damage, the three point loading was applied to the prepared reinforced concrete beam specimen. The optimal frequency band was determined which resulted in the structural condition for that the four statistical indices were investigated with various crack severities in several sub-frequency bands. The optimal frequency band was determined as 161–215 kHz. Further, the crack healing performance was investigated with a pre-evaluated optimal frequency band using the statistical damage indices. The damage indicators RMSD, MAPD, and CC were appropriate for the evaluation of damage severity; however Cov was appropriate for damage severity evaluation in lesser amounts in a sub-frequency band. The evaluated damage indicators RMSD, MAPD, Cov, and CC successfully signified the crack healing by the bacterial incorporation in concrete structures. The SEM and XRD tests were performed for the confirmation of calcite deposition at the cracks. The developed concept is resulted in significantly evaluating the healing quality of the cracks by bacterial incorporation over time.