Influence of PZT patch geometry and location on electro-mechanical Impedance signatures of corroded square steel bars
Mallika Alapati1 and Soujanya Jakkula1
Corresponding Author : Mallika Alapati
Recieved : 25-November-2024; Revised : 25-January-2026; Accepted : 29-January-2026
Abstract
Damage mechanisms such as corrosion in steel structural members need to be detected at an early stage to prevent flexural failures and to enable timely preventive measures that enhance the residual service life of the structure. Corrosion reduces the effective cross-sectional area of structural elements, leading to increased stress concentrations. In recent years, sensor-based technologies have gained significant attention for detecting, localizing, and characterizing such damage in structures. The objective of the present study is to exploit the coupling property between the mechanical impedance of the host structure and a lead zirconate titanate (PZT) patch. The study further investigates variations in electro-mechanical impedance (EMI) signatures for real-time corrosion monitoring. Numerical analyses are carried out on a smart cantilever beam instrumented with a PZT patch, considering both corroded and uncorroded conditions. The numerical results are presented and discussed for two different patch lengths, multiple patch locations, and varying corrosion depths. The influence of patch geometry, specifically patch length, on admittance signatures resulting from corrosion damage in the host steel structure is evaluated. Harmonic excitation results indicate that shifts and increases in conductance peak magnitudes are sensitive to both corrosion depth and patch length. When the patch length is doubled, the conductance peak magnitudes increase, demonstrating that the actuating and sensing capabilities of the EMI technique are strongly influenced by patch length. Furthermore, the effect of patch location on sensitivity is found to be insignificant, which can be attributed to the relatively small length of the steel bar considered in this study.
Keywords
Electro-mechanical impedance, Corrosion monitoring, PZT sensor, Structural health monitoring, Conductance signature, Steel structures.
Cite this article
Alapati M, Jakkula S. Influence of PZT patch geometry and location on electro-mechanical Impedance signatures of corroded square steel bars. International Journal of Advanced Technology and Engineering Exploration. 2026;13(136):366-379. DOI : 10.19101/IJATEE.2024.111102084
[1] Na WS, Baek J. A review of the piezoelectric electromechanical impedance based structural health monitoring technique for engineering structures. Sensors. 2018; 18(5):1-18.
[2] Ju M, Dou Z, Li JW, Qiu X, Shen B, Zhang D, et al. Piezoelectric materials and sensors for structural health monitoring: fundamental aspects, current status, and future perspectives. Sensors. 2023; 23(1):1-20.
[3] Yang Y, Zhang Y, Tan X. Review on vibration-based structural health monitoring techniques and technical codes. Symmetry. 2021; 13(11):1-18.
[4] Cui E, Zuo C, Fan M, Jiang S. Monitoring of corrosion-induced damage to bolted joints using an active sensing method with piezoceramic transducers. Journal of Civil Structural Health Monitoring. 2021; 11(2):411-20.
[5] Giurgiutiu V. Structural health monitoring with piezoelectric wafer active sensors. Academic Press; 2014.
[6] Fan X, Li J, Hao H. Review of piezoelectric impedance based structural health monitoring: physics-based and data-driven methods. Advances in Structural Engineering. 2021; 24(16):3609-26.
[7] Divsholi BS, Yang Y. Application of PZT sensors for detection of damage severity and location in concrete. In smart structures, devices, and systems IV 2008 (pp. 254-61). SPIE.
[8] Chowdary DY, Harshitha C, Alapati M. Parameters influencing PZT sensing in structural health monitoring. Materials Today: Proceedings. 2022; 62:1883-8.
[9] Maurya KK, Rawat A, Jha G. Smart materials and electro-mechanical impedance technique: a review. Materials Today: Proceedings. 2020; 33:4993-5000.
[10] Parida L, Moharana S. A comprehensive review on piezo impedance based multi sensing technique. Results in Engineering. 2023; 18:1-11.
[11] Budoya D, De CB, Campeiro L, Da SR, De FE, Baptista F. Analysis of piezoelectric diaphragms in impedance-based damage detection in large structures. Proceedings. 2017; 2(3):1-6.
[12] Shelgaonkar T, Narayanan A, Basappa U. A review on the impact of thermal effects on electro-mechanical impedance technique-based structural health monitoring. Journal of Nondestructive Evaluation. 2025; 44(3):76.
[13] Raju J, Bhalla S, Visalakshi T. Pipeline corrosion assessment using piezo-sensors in reusable non-bonded configuration. NDT & E International. 2020; 111:1-16.
[14] Li W, Liu T, Zou D, Wang J, Yi TH. PZT based smart corrosion coupon using electromechanical impedance. Mechanical Systems and Signal Processing. 2019; 129:455-69.
[15] Nolan EC, Anton SR. Electromechanical impedance based structural health monitoring measuring system in the millisecond timescale. In health monitoring of structural and biological systems XIV 2020 (pp. 297-307). SPIE.
[16] Liang C, Sun FP, Rogers CA. An impedance method for dynamic analysis of active material systems. Journal of Vibration and Acoustics. 1994; 116(1):120-8.
[17] Zhu H, Luo H, Ai D, Wang C. Mechanical impedance-based technique for steel structural corrosion damage detection. Measurement. 2016; 88:353-9.
[18] Fan L, Shi X. Techniques of corrosion monitoring of steel rebar in reinforced concrete structures: a review. Structural Health Monitoring. 2022; 21(4):1879-905.
[19] Parmar N, Vinaykumar CH. Corrosion assessment in steel reinforcement using piezoelectric sensor for service life prognosis of reinforced concrete structures. Journal of Information Systems Engineering and Management. 2025; 10(18):133-40.
[20] Gayakwad H, Thiyagarajan JS. Structural damage detection through EMI and wave propagation techniques using embedded PZT smart sensing units. Sensors. 2022; 22(6):1-25.
[21] Thoriya A, Vora T, Nyanzi P. Pipeline corrosion assessment using electromechanical impedance technique. Materials Today: Proceedings. 2022; 56:2334-41.
[22] Reddypogu SS, Alapati M. Numerical investigation on EMI signatures in pipes with varied damage levels. Materials Today: Proceedings. 2021; 45:3452-7.
[23] Sowjanya J, Alapati M. Influence of patch location on damage detection of smart bar using EMI technique. i-Manager's Journal on Civil Engineering. 2019; 9(2):62-8.
[24] Luo Z, Deng H, Li L, Luo M. A simple PZT transducer design for electromechanical impedance (EMI)-based multi-sensing interrogation. Journal of Civil Structural Health Monitoring. 2021; 11(1):235-49.
[25] Ahmadi J, Feirahi MH, Farahmand-tabar S, Fard AH. A novel approach for non-destructive EMI-based corrosion monitoring of concrete-embedded reinforcements using multi-orientation piezoelectric sensors. Construction and Building Materials. 2021; 273:1-17.
[26] Huynh TC, Dang NL, Kim JT. Advances and challenges in impedance-based structural health monitoring. Structural Monitoring and Maintenance. 2017; 4(4):301-29.
[27] Talakokula V, Bhalla S, Ball RJ, Bowen CR, Pesce GL, Kurchania R, et al. Diagnosis of carbonation induced corrosion initiation and progression in reinforced concrete structures using piezo-impedance transducers. Sensors and Actuators A: Physical. 2016; 242:79-91.
[28] Lim YY, Soh CK. Electro-mechanical impedance (EMI)-based incipient crack monitoring and critical crack identification of beam structures. Research in Nondestructive Evaluation. 2014; 25(2):82-98.
[29] Nestorović T, Trajkov M, Garmabi S. Optimal placement of piezoelectric actuators and sensors on a smart beam and a smart plate using multi-objective genetic algorithm. Smart Structures and Systems, An International Journal. 2015; 15(4):1041-62.
[30] Oh TK, Kim J, Lee C, Park S. Nondestructive concrete strength estimation based on electro-mechanical impedance with artificial neural network. Journal of Advanced Concrete Technology. 2017; 15(3):94-102.
[31] Gomasa R, Talakokula V, Jyosyula SK, Bansal T. Integrating electro-mechanical impedance data with machine learning for damage detection and classification of blended concrete systems. Construction and Building Materials. 2024; 445:1-24.
[32] De OMA, Monteiro AV, Vieira FJ. A new structural health monitoring strategy based on PZT sensors and convolutional neural network. Sensors. 2018; 18(9):1-21.
[33] Alazzawi O, Wang D. Damage identification using the PZT impedance signals and residual learning algorithm. Journal of Civil Structural Health Monitoring. 2021; 11(5):1225-38.
[34] Nguyen KD, Ho DD, Kim JT. Damage detection in beam-type structures via PZT's dual piezoelectric responses. Smart Structures and Systems. 2013; 11(2):217-40.