Electromechanical Impedance Method Research Articles

A comparison of signal processing techniques for impedance-based damage characterization in carbon fibers under noisy inspections

Among several structural health monitoring (SHM) systems, the electro-mechanical impedance (EMI) method is an effective failure detection approach in composite components. In the EMI method, damage detection is achieved by comparing the behaviour of piezoelectric impedance signatures, which are related mathematically to the mechanical impedance of the host structure. Although many studies have proved the effectiveness of the EMI method on composites, many practical issues such signal changes caused by noise and vibrations have limited its use in real-life applications. This work presents an experimental analysis of white noise effects on the impedance monitoring of a carbon fibre reinforced plastic composite plate, by applying the correlation coefficient deviation metric (CCDM) and cross-correlation square deviation (CCSD) index on the response signal of a pitch-catch mode piezoelectric transducer. Experimental results revealed that the CCSD was more sensitive to damage detection under noisy inspections.

Numerical and experimental investigation of electro-mechanical impedance based concrete quantitative damage assessment

This paper presents a numerical and experimental investigation of the concrete quantitative damage assessment using the smart aggregate (SA) sensor based on the electro-mechanical impedance method. In the numerical simulation, a concrete cube finite element model with an embedded SA sensor is established using concrete damaged plasticity constitutive model to simulate the damage process under uniaxial compression. The concrete damage degree is evaluated using the conductance signatures of the embedded SA sensor and damage volume ratio (DVR). In the experimental study, three concrete cubes are casted and subjected to compressive loading. The experimental study verifies the numerical simulation model by comparing the root mean square deviation (RMSD) indices of conductance signals. Furthermore, the DVR is proposed as an effective damage evaluation index. The relationship curve between the DVR and the RMSD is fitted. The results illustrate that the RMSD index of the SA sensor and the DVR of the concrete have a linear relationship. The level of concrete damage can be quantitatively evaluated by RMSD index according the relationship between the RMSD and DVR.

Monitoring of Grouting Compactness in Tendon Duct Using Multi-Sensing Electro-Mechanical Impedance Method

The structural integrity of post-tensioning prestressed concrete structures with tendon ducts highly depends on the grouting quality in construction. This paper proposes a real-time approach to monitoring the grouting compactness in tendon ducts using the multi-sensing electro-mechanical impedance (EMI) method. When Lead Zirconate Titanate (PZT) transducers with different pre-selected dimensions are serially connected and mounted on a structure at distributed locations, each PZT provides unique resonance frequency coupled with the local structural physical property. Therefore, the impedance with multiple peaks of the serially connected multiple PZTs can be captured during a single measurement, which significantly simplifies the measurement procedure and reduces the data processing time. In addition, the wiring for the PZT sensors is also simplified. In this research, the feasibility of the proposed method was experimentally and numerically investigated to monitor the grouting compactness in a tendon duct specimen. The 3-dB mean absolute percentage deviation (MAPD) was applied to quantify the variations of the impedance signatures measured from five different grouting levels. Both experimental and numerical results verify the feasibility of using the proposed method for monitoring the grouting compactness in tendon ducts.

Damage Detection of Epoxied Joint Model in Precast Concrete Segmental Bridges Using PZT Technology

AbstractThe feasibility of integrating the wave propagation (WP) method with the electromechanical impedance (EMI) method in damage diagnosis of joints in precast concrete segments under shear load...

Structural Health Monitoring for Concrete Structure using Impedance Chip

Structural Health monitoring plays a vital role in all generations for the safety of life and property. The method of Electromechanical Impedance (EMI) method and sensors are used in damage detection of civil and mechanical structures. The structure deteriorates due to ageing and environmental factors. This study represents the detection of damage in concrete structure using piezo electric transducer and EMI method. The piezo sensor is bonded to the concrete structure using epoxy resin and damage is created by using flexural testing machine. The force is applied using flexural testing machine at different KiloNewton. The output from the impedance chip is noted at undamaged state and at all levels of applied force. The impedance, admittance, conductance and susceptance curves are drawn with different levels of frequency. Root mean square deviation is also calculated for the detection of damage. The results conclude that Impedance chip is highly reliable and accurate in damage detection of concrete structure.

Analytical Model of the Electro-Mechanical Impedance Response of Frame Structures with L-Shaped Beams

ABSTRACTThe electro-mechanical impedance (EMI) method has been accepted as an effective technique for detecting damages in the Structural health monitoring (SHM). EMI at any point of the structure depends on material properties, geometry and boundary conditions that all appears in dynamic stiffness of the structure. In spite of the expensive experimental methods for measuring the mechanical impedance, or the cheaper one electromechanical impedance, of structures, various analytical methods could be substitutions for them. In this paper, an analytical method is developed to obtain the EMI response of L-shaped beams through calculating the dynamic stiffness of the structure. To verify the model, an experimental setup with an embedded piezoelectric wafer active sensor (PWAS) is carried out. The results have shown that EMI and its real part, extracted by the current analytical method, are with good agreement of the experimental results. Also, the dynamic stiffness of the structure directly depends on the mode shapes of the structure and its natural frequencies in terms of the excitation frequency. The peaks of the real part of the EMI results related to the coincidence between agitation frequency value and natural frequencies of the structure.

Structural Health Monitoring of Timber Using Electromechanical Impedance (EMI) Technique

Nowadays, the electromechanical impedance method has been widely used in the field of structural healthy monitoring, especially for the concrete and steel materials. However, the electromechanical impedance studies on damage detection for timber are limited due to the anisotropic and ununiform biomaterial properties. As a low‐cost and environment‐friendly building material, timber has been widely used in the construction. Thus, it is beneficial to develop electromechanical impedance technique for structural healthy monitoring of timber so as to ensure the stability and safety of the entire timber structures. In this paper, two damage factors, i.e., the damage location factor and the damage size factor of timber specimens are investigated by using the electromechanical impedance method. The method is implemented by using a patch of Lead Zirconate Titanate transducer both as an actuator to generate stress waves and a sensor to detect stress waves after propagating across the timber specimens. Then, the damage index‐root mean square deviation is employed to evaluate the damage severity of the timber specimens. The results indicate that the damage index changes consistently with the change of damage location and size factors, and the proposed method using electromechanical impedance technique can efficiently estimate the damage and its severity.

Structural Damage Recognition Based on the Finite Element Method and Quantum Particle Swarm Optimization Algorithm

Structural damage recognition is always the concerned focus in many fields like aerospace, petroleum and petrochemical industry, industrial production and civil life. For damage recognition in complex structure or structural interior, especially somewhere sensors can’t go, minor damage is often hard identified by not only traditional nondestructive testing methods like ultrasonic testing, radiographic testing, magnetic particle testing, penetrant testing, eddy current testing, but also the current popular ultrasonic guided wave based on the piezoelectric wafer, electromagnetic acoustic transducer or magnetostrictive sensor, which is mainly because the response signals are always affected by many structural features. In this article, the advanced global search algorithm, quantum particle swarm optimization algorithm is first combined with the finite element method to accurately recognize the structural damage based on the conductance-frequency spectrum resulted from electromechanical impedance method. Meanwhile, the objective function is designed to compare the difference of peak frequency variations in the experiment and finite element calculation respectively. By adopting the stiffness reduction method of the elements near the structural damage, the identification efficiency is largely improved for no need to repeatedly partition the model grid. And after multiple iteration optimization of the artificial intelligence algorithm - quantum particle swarm optimization algorithm, the identification error of damage parameters including location and degree can be reduced to below 4 percent. Therefore, the combination of finite element method and quantum particle swarm optimization algorithm is quite effective for guaranteeing high accuracy and efficiency for damage parameters’ recognition in complex structures

A novel method for diagnosing defective PZT-Substrate bonding in electromechanical (EM) impedance technique

Surface mounted PZT (Lead Zirconate Titanate) patches are extensively used to monitor the localized and distributed damage in concrete structures in recent times. To avoid the misinterpretation of damage in the real structures the development of reliable techniques for detection and detailing of de bonding is necessary. In this study the electro mechanical impedance method is employed to detect the partial de bonding of surface mounted PZT patch. The effect of defective bonding of PZT patch on electrical impedance (EI) response spectrum investigated by combining experimental and numerical approaches. The investigation is carried out in two steps. In the first step, the experiments are carried with surface mounted PZT patches attached to the concrete substrate in perfectly bonded condition and 10% de bonded condition and the EI response spectrum is extracted in both perfectly bonded and partially de bonded conditions. The influence of finite size of substrate is eliminated from EI response spectrum to identify the influence of de bonding alone on EI response spectrum. In the second step, a numerical model is developed for a PZT patch attached to a concrete substrate using COMSOL Multiphysics. The developed numerical model is then calibrated using experimental studies, surface mounted PZT patches with different de bonding percentages are studied and their influence on the electromechanical impedance response of the bonded PZT is explored using the calibrated numerical model. The current study proposes a new effective method for diagnosing defective PZT-substrate bonding in surface mounted PZT patches attached to concrete substrate.

A spherical smart aggregate sensor based electro-mechanical impedance method for quantitative damage evaluation of concrete

In this study, the concrete damage induced by compression is evaluated quantitatively using spherical smart aggregate sensor based on electro-mechanical impedance method. The sensitivity of the spherical smart aggregate sensor embedded in concrete cubes is investigated by comparing the electrical signals recorded during the compressive process with those of the smart aggregate sensor embedded in concrete cubes. Furthermore, the finite element model of concrete cube with an embedded spherical smart aggregate sensor is developed to simulate the concrete compressive tests. The concrete damaged plasticity constitutive model is utilized to simulate the concrete damage process. The numerical model is verified with the experimentally measured compressive test results. Finally, the damage volume ratio is presented to quantify the damage level of concrete based on the numerical model. The relationship between the root mean square deviation index of the conductance signatures obtained from experiments and the damage volume ratio computed by numerical simulation is established to quantify the concrete damage level. The results show that the spherical smart aggregate sensor is more sensitive than the smart aggregate sensor in monitoring the three-dimensional concrete structures. The proposed empirical fitting curve can effectively evaluate the concrete damage level quantitatively.

Monitoring of multi-bolt connection looseness using entropy-based active sensing and genetic algorithm-based least square support vector machine

Abstract Looseness detection of bolted connections is an essential industrial issue that can reduce the maintenance and repair costs caused by joint failures; however, current loosening detection methods mainly focus on the single-bolt connection. Even though several methods, such as the vibration-based method and electro-mechanical impedance (EMI) method, have been employed to detect multi-bolt looseness, while they are easily affected by environmental issues. Therefore, the main contribution of this paper is to detect loosening of the multi-bolt connection through the PZT-enabled active sensing method, which has several merits including easy-to-implement, low cost, and good ability of anti-environment disturbance. Since the current indicator of the active sensing, namely the signal energy is insensitive to multiple damages, we developed a new damage index (DI) based on the multivariate multiscale fuzzy entropy (MMFE). Subsequently, the maximum relevance minimum redundancy (mRMR) was used to select significant features from the MMFE-based DI to construct the new datasets. After feeding the new datasets into the genetic algorithm-based least square support vector machine (GA-based LSSVM), we trained a classifier to detect loosening of the multi-bolt connection. Finally, repeated experiments were conducted to demonstrate the effectiveness of the proposed method, which can guide future investigations on bolt looseness detection.

Co-Integration-Based Compensation Technique for Dynamic Load Effects on the Electro-mechanical Impedance Method

Abstract The electro-mechanical (EM) admittance signals acquired from piezoelectric transducers (PZT) surface bonded to the host structure are often used for structural health monitoring (SHM). However, it is well known that the method is susceptible to contamination from environmental and operational conditions. This paper introduces a co-integration method to remove dynamic load effects from electro-mechanical admittance data. The proposed method is based on the concept of co-integration that is partially built on the analysis of the non-stationary behavior of time series. Instead of directly using admittance signatures of PZT for damage detection, the analysis of the co-integrated residual obtained from the co-integration procedure of EM admittance responses and the resonant peaks frequency of the real part of admittance (conductance) are chosen as co-integrated variables. The experiments of aluminum beam bolt loosening identification, which is under dynamic stress, were carried out to verify the effectiveness of the proposed method. The results showed that the method can isolate damage-sensitive features from stress variations, so as to successfully detect the existence of damage.

Instantaneous monitoring the early age properties of cementitious materials using PZT-based electromechanical impedance (EMI) technique

The use of piezoelectric materials based Electromechanical Impedance (EMI) technique for monitoring the hydration of cementitious materials has caught much attention recently. However, very few literatures have explored the feasibility of using this method on monitoring the stiffness development and compressive strength gain at the very early age properties (4th–8th h) of cementitious materials. This research serves as a comprehensive study to verify the reliability of using lead zirconate titanate (PZT) based EMI method in monitoring the compressive strength gain and elastic modulus of mortar at both very early age (4th–8th h) and early age (1st, 3rd, and 7th day). Extensive experiments and data analysis have been done on ten different mixes with various water-to-cement ratio and Type I & III cement. The EMI signatures are measured for each sample at the period of interest, and post-processed with three statistic model including the root mean square deviation (RMSD), correlation coefficient deviation (CCD), and mean absolute percentage deviation (MAPD) as indices. To examine the correlation and linearity between the compressive strength/elastic modulus obtained via conventional cubic testing using ASTM C109 and the EMI indices, a linear least square regression analysis is performed. As the authors postulated, all the mixes display a good linear correlation of R2. Among all three statistical indices, RMSD index is proved as the most accurate statistical index on strength gain monitoring of cementitious materials. The results indicated the feasibility of using piezoelectric-based EMI method for monitoring the cementitious material’s strength gain at very early age, regardless the concrete mix design.

Feature extraction approach insensitive to temperature variations for impedance‐based structural health monitoring

Structural health monitoring (SHM) based on the electromechanical impedance (EMI) has been pointed out as a promising method for detecting structural damage. However, practical problems such as the effects of temperature variation on the electrical impedance signatures of piezoelectric transducers have made it difficult to effectively apply this method of detecting damage in real structures. Therefore, in order to contribute to the effective application of the EMI method in real structures, this study presents a new feature extraction approach insensitive to temperature variations. The proposed method is based on the Akaike statistical criterion algorithm, which extracts the number of significant resonance peaks from the electrical impedance signatures. Tests were performed on an aluminium bar with different damage sizes and under different temperatures. The experimental results indicate that the proposed method is capable of detecting and quantifying structural damage in environments under temperature variation.

A chromatic technique for structural damage detection under noise effects based on impedance measurements

Structural health monitoring (SHM) based on electromechanical impedance (EMI) measurements has been extensively studied in recent years and stands out as an effective damage detection approach. The EMI method commonly uses low-cost piezoelectric transducers and structural diagnosis can be accomplished by analyzing the changes in the impedance measurements from the transducers attached to the host structure. Although many studies have proved the effectiveness of the EMI method, one of the most reported problems is the variations in the impedance caused by external noise, which can alter the impedance measurements and limit the effectiveness of the detection and quantification of damage using conventional basic damage indices. Therefore, this paper proposes a new approach for structure feature extraction in noisy environments based on the chromatic signal processing technique associated with the Hinkley criterion, thus aiming to expand the applicability of the EMI method to real applications. Experimental tests were carried out on aluminum and carbon fiber composite plates subjected to various signal noise levels. The experimental results indicate that the proposed approach is more effective for damage detection compared to the basic indices commonly reported in the literature.

Bond-Slip Monitoring of Concrete Structures Using Smart Sensors-A Review.

Concrete structures with various reinforcements, such as steel bars, composite material tendons, and recently steel plates, are commonly used in civil infrastructures. When an external force overcomes the strength of the bond between the reinforcement and the concrete, bond-slip will occur, resulting in a relative displacement between the reinforcing materials and the concrete. Monitoring bond health plays an important role in guaranteeing structural safety. Recently, researchers have recognized the importance of bond-slip monitoring and performed many related investigations. In this paper, a state-of-the-art review on various smart sensors based on piezoelectric effect and fiber optic technology, as well as corresponding techniques for bond-slip monitoring is presented. Since piezoelectric sensors and fiber-optic sensors are widely used in bond-slip monitoring, their principles and relevant monitoring methods are also introduced in this paper. Particularly, the piezoelectric-based bond-slip monitoring methods including the active sensing method, the electro-mechanical impedance (EMI) method and the passive sensing using acoustic emission (AE) method, and the fiber-optic-based bond-slip detecting approaches including the fiber Bragg grating (FBG) and the distributed fiber optic sensing are highlighted. This paper provides guidance for practical applications and future development of bond-slip monitoring.

A PZT-Based Electromechanical Impedance Method for Monitoring the Soil Freeze⁻Thaw Process.

It is important to conduct research on the soil freeze–thaw process because concurrent adverse effects always occur during this process and can cause serious damage to engineering structures. In this paper, the variation of the impedance signature and the stress wave signal at different temperatures was monitored by using Lead Zirconate Titanate (PZT) transducers through the electromechanical impedance (EMI) method and the active sensing method. Three piezoceramic-based smart aggregates were used in this research. Among them, two smart aggregates were used for the active sensing method, through which one works as an actuator to emit the stress wave signal and the other one works as a sensor to receive the signal. In addition, another smart aggregate was employed for the EMI testing, in which it serves as both an actuator and a receiver to monitor the impedance signature. The trend of the impedance signature with variation of the temperature during the soil freeze–thaw process was obtained. Moreover, the relationship between the energy index of the stress wave signal and the soil temperature was established based on wavelet packet energy analysis. The results demonstrate that the piezoceramic-based electromechanical impedance method is reliable for monitoring the soil freezing and thawing process.

Comparative analysis of signal processing techniques for impedance-based SHM applications in noisy environments

Structural health monitoring (SHM) systems have been extensively studied in recent decades to determine the health statuses of mechanical, naval and aerospace engineering components. Currently, one of the most promising non-destructive tests for the detection of structural damage is the electromechanical impedance (EMI) technique, which uses low-cost, surface-bonded piezoelectric transducers operating both as sensors and actuators. Although many studies have reported the effectiveness of the EMI method, numerous practical issues, such as signal noise effects caused by environmental conditions, may severely affect the detection and quantification of damage. Therefore, this paper presents a comparative analysis of three signal processing techniques used in the context of the EMI method, which have the potential to enhance the detection of structural damage under environmental signal noise effects. These signal analysis methods include (i) damage indices, such as the correlation coefficient deviation metric, computed directly on impedance signatures; (ii) the wavelet transform computed on transducer response signals in the time domain; and (iii) a novel approach of damage feature extraction in the EMI method based on the Hinkley criterion. Experimental tests were carried out to analyse the three signal processing techniques on a damaged aerospace composite carbon fibre structure subjected to various signal noise levels. The experimental results revealed that conventional damage indices and wavelet transform were significantly affected by noise, whereas the proposed approach based on the Hinkley criterion was more effective for detecting damage in noisy environments.

Use of the electromechanical impedance method in the detection of inclusions: application to mammary tumors

Breast cancer is a public health problem and has the highest incidence and mortality in the female population worldwide. Early detection of breast cancer is essential for reducing the morbidity and mortality associated with this disease. Some methods for detecting breast tumors include ultrasonography, magnetic resonance imaging, positron emission tomography, tomosynthesis, and mammography, which are recommended as screening techniques. Each method has its advantages and disadvantages, such as discomfort to the patient during examination, possible reactions to the contrast agent, radiation emission, operator dependence for the analysis of results, difficulty of detection in dense tissues, lack of access for people with disabilities or low mobility, high cost, and radioactive waste production. The main objective of this work is to apply the electromechanical impedance method to the detection of inclusions so that it can be used as an alternative to existing techniques for the detection of breast tumors. The application of the electromechanical impedance method using piezoelectric transducers, acting simultaneously as sensors and actuators, coupled to the analyzed structure allows the monitoring of mass, rigidity, and/or damping variations, and consequent detection of inclusions. The detection of inclusions is possible owing to damage metrics, which are statistical parameters capable of numerically representing the difference between two measurements before and after damage. In this work, silicone samples and phantom breast models were analyzed. In addition, it was observed that external heating imposed on the models and the presence of heat generation in the inclusions aided detection. This work presents important contributions in the analysis of structural behavior, expanding the applications of damage detection techniques to hyperplastic materials.

Interface monitoring of steel-concrete-steel sandwich structures using piezoelectric transducers

Abstract Steel-concrete-steel (SCS) sandwich structures have important advantages over conventional concrete structures, however, bond-slip between the steel plate and concrete may lead to a loss of composite action, resulting in a reduction of stiffness and fatigue life of SCS sandwich structures. Due to the inaccessibility and invisibility of the interface, the interfacial performance monitoring and debonding detection using traditional measurement methods, such as relative displacement between the steel plate and core concrete, have proved challenging. In this work, two methods using piezoelectric transducers are proposed to detect the bond-slip between steel plate and core concrete during the test of the beam. The first one is acoustic emission (AE) method, which can detect the dynamic process of bond-slip. AE signals can be detected when initial micro cracks form and indicate the damage severity, types and locations. The second is electromechanical impedance (EMI) method, which can be used to evaluate the damage due to bond-slip through comparing with the reference data in static state, even if the bond-slip is invisible and suspends. In this work, the experiment is implemented to demonstrate the bond-slip monitoring using above methods. Experimental results and further analysis show the validity and unique advantage of the proposed methods.