PSI - Issue 70

Arpit Singh et al. / Procedia Structural Integrity 70 (2025) 580–587

587

The root mean square deviation indicates the deviation in conductance with increasing levels of artificial damage. As illustrated in Fig. 7, up to the incipient damage stage (D3), the RMSD shows a change of about 4%. After a continued damage progression up to D9, the RMSD will increase by some 15%, corresponding to the moderate damage stage. Beyond D9, the deviation in the RMSD diminishes compared to previous stages, marking the development of severe damage. This categorization emphasizes the reduced sensitivity of stiffness change with increasing damage levels and also enhances the efficacy of the EMI technique in monitoring early-stage structural

deterioration. 5. Conclusion

This study demonstrates that embedded PZT sensors and a novel 2D electromechanical impedance (EMI) model are effective for detecting and monitoring damage in concrete structures. From experiments, the group identified definite thresholds for various damage levels 4.22% (early-stage), 9.8% (moderate), and above 9.8% (severe) by examining EMI data with RMSD parameters. These thresholds allow engineers to precisely assess a structure's condition at each level of damage, enabling them to catch potential problems early and take action before issues develop. The quantified leftward and upward displacements of conductance-frequency spectra are linearly proportional to loss in stiffness, providing an objective measure for the degree of damage. By sensing these thresholds, electrical impedance tomography sends early warning of slight deviations in stiffness, allowing preventive maintenance to counteract and prevent catastrophic collapse and to achieve optimal lifecycle optimization. This evidence-based method integrates EMI response behaviors with action-oriented damage intelligence to provide sustainable infrastructure resilience through timely, evidence-based interventions. References Ai, D., Zhu, H., Luo H., 2016, Sensitivity of embedded active PZT sensor for concrete structural impact damage detection, Construction and Building Material, vol. 111, pp. 348-357. Bhalla, S., King Soh, C., 2004, Structure Health Monitoring by Piezo-Impedance Transducers. I: Modelling, Journal of Aerospace Engineering, Vols 17, No 4. Bhalla, S., K. Soh, C., 2003, S. Bhalla and C. K. SOH, 2003, STRUCTURAL HEALTH MONITORING BY PIEZO-IMPEDANCE. D. Kuhn, J., R.Soni, S., 2009, A Design of Experiments Approach to Determing Structural Health Monitoring Sensor Durability. E. Chalioris, C., G. Karayannis, C., M. Angeli, M., A. Papadopoulos, N., J. Favvata, M., P. Providakis, C., 2016, Applications of smart piezoelectric materials in a wireless admittance monitoring system (WiAMS) to Structures Tests in RC elements, vol. 5, pp. 1-18. E. Chalioris, C., G. Karayannis, C., M. Angeli, M., A. Papadopoulos, N., J. Favvata, M., P. Providakis, C., 2016, Applications of smart piezoelectric materials in a wireless admittance monitoring system (WiAMS) to Structures Tests in RC elements, vol. 5, pp. 1-18. F. Su, Y., Han, G., Amran, A., Nantung, T., Lu, N., 2020, Instantaneous monitoring the early age properties of cementitious materials using PZT based electromechanical impedance (EMI) technique, Journal of Intelligent Material Systems and Structures, vol. 32. Guangping, L., Mingzhang, L., Jinping, H., Weijie, L., 2023, “Early -age concrete stregth monitoring using smart aggregate based on electromechanical impedance and machine learning,” Mechanical system and signal Processing, vol. 186. J. Saravanan, T., Balamonica, K., B. Priya, C., Gopalakrishnan, N., Murthy, S., 2017, Piezoelectric EMI – Based Monitoring of Early Strength Gain in Concrete and Damage Detection in Structural Components, Journal of Infrastructure Systems, vol. 23. Lin, B., Giurgiutiu, V., 2006, Modeling and testing of PZT and PVDF piezoelectric wafer active sensors, Smart Materials and Structures. Liu, P., Wang, W., Chen, Y., Feng X., Miao, L., 2017, Concrete damage diagnosis using electromechanical impedance technique, Procedia Structural Integrity, vol. 5, pp. 171-178. Narayanan, A., V. Subramaniam, K., 2015, Experimental evaluation of load-induced damage in concrete from distributed microcracks to localized cracking on electro-mechanical impedance response of bonded PZT, Construction and Building Materials, vol. 105, pp. 536-544. Pereira, P. E. C., Ruas, S. R., Silva, V.R., 2024, Enhancements and Future Horizons in Electromechanical Impedance-Based Damage Detection: A Comprehensive Systematic Review, Journal of Engineering Science and Technology, pp 108-112. Quoc-Bao, T., Quang-Quang, P., Ngoc-Lan, P., Jeong- Tae, K., 2024, “Integrating the Capsule -like Smart Aggregate-Based EMI Technique with Deep Learning for Stress Assessment in Concrete,” Sensors, vol. 24(14). Singh, S. K., Malinowski, P. H., 2022, An innovative data-driven probabilistic approach for damage detection in Electromechanical Impedance Technique, Composite structure, vol 295. Zhu, H., Luo,H., Ali, D., Wang, C., 2016, Mechanical impedance-based technique for steel structural corrosion damage detection, Construction and Building Materials, pp 472-482. Zhu, H., Luo, H. Ai, D., Wang, C., June,2016, Mechanical impedance-based techniques for steel structural corrosion damage detection, p. 1033.