PSI - Issue 70

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

581

Keywords: Root mean square deviation, Lead-zirconium titanate transducers, Electro-mechanical impedance technique.

1. Introduction Civil infrastructure is an important long-term investment for any country, which contributes significantly to both economic development and social progress. In the recent past, SHM has been attempted using low-frequency vibration records (Pandey and Biswas 1994; Farrar and Jauregui 1998), static displacements (Banan et al. 1994). These methods mostly utilize a combination of traditional sensors such as accelerometers or strain gauges which are only appropriate for load or strain history measurement. However, smart materials such as piezoelectric materials, optical fibers, shape memory alloys, and magneto-strictive materials have emerged. These introduce new dimensionality to the SHM by enabling systems with reduced sizes, increased resolutions, quicker response times, and higher reliability. Structural health monitoring is a crucial phase in the methodical examination and assessment of structures with respect to their integrity, safety, and dependability. This is particularly important for infrastructure, such buildings, bridges, and dams, where concealed deterioration can lead to failure. The Electro-mechanical impedance method, the lead zirconate titanate patch attached to surface, which serve as sensor and transducer, quantify the electric impedance through coupling effect which has direct correlation with the host structure's mechanical impedance, thus enabling damage to the structure to be detected through monitoring the change in the measured Electro-mechanical impedance signature. The electro-mechanical impedance method has also been used in different areas of engineering. Pereira et al. (2024) reported a review of recent five years of research to illustrate how effective damage detection enhances maintenance strategies. They identified EMI methods to be useful in non-destructive testing due to their low cost and sensitivity. The majority employed advanced signal processing, with more than a quarter using machine learning. Temperature fluctuation and erratic sensor performance challenges were reported, as well as limitations in utilizing these methods for real industrial application, which requires further effort. S K Singh et al. (2022) showed that choosing optimal frequency ranges (1 kHz – 2 MHz) enhances damage detection accuracy in structural health monitoring considerably. From analysis of impedance data by a statistical approach, they accurately discriminated between undamaged and damaged structures. The research presented an approach combining conductance (G) and resistance (R) testing into one damage indicator, which successfully identifies damage location, assesses severity (even at initial stages), and is adaptable to wide-range materials. This method highlights the important position of frequency optimization and combined parameters for accurate, versatile structural analysis. Su et al. (2020) investigated the use of piezoelectric (PZT) electromechanical impedance (EMI) methods to assess the evolving properties of cementitious composites during their early curing stages, demonst rating the technique’s sensitivity to microstructural changes in hydrating materials. It establishes a clear relationship between EMI values and controlled damage, identifying RMSD as the most effective statistical indicator. Results reveal that the procedure can be implemented for a wide range of different cements and water-to-cement ratio values, allowing room for more study on the effects of environmental factors and a range of diverse mixes for field implementation. T. Jothi Saravanan et al. (2017) piezoelectric smart aggregate use in concrete to monitor early strength gain and damage identification. It establishes a relationship between electromechanical impedance (EMI) signatures and strength of concrete, enhancing formwork removal planning and conclude the peaks of conductance vs frequency curves show a rightward shift of amplitudes during strength gain. Peng Liu et al. (2017) studied the applicability of embedded piezoelectric sensors for damage diagnosis of freezing thawing cycles and cracks in concrete. The research established that the impedance spectra of the sensors have a good correlation with damage levels, especially at the 100-150 kHz frequency range, showing a valid means for real-time monitoring of concrete integrity. The Root Mean Square Deviation index has been confirmed to be a valid measure for damage severity quantification in structural systems. In contemporary structural health monitoring, lead zirconate titanate transducers play key roles, allowing constant evaluation of structural integrity through real-time impedance measurement. Such sensors enable low-cost maintenance approaches by allowing early defect detection, thus improving operational safety and extending structural lifespan. Their integration ensures sustainable infrastructure management by emphasizing early detection of defects and timely corrective measures to counter potential failures, consistent with the changing requirements of resilient civil engineering practice.