Structural Health Monitoring (SHM) has increasingly shifted toward smart-material-based solutions capable of providing continuous and real-time assessment of structural integrity. Among these approaches, the Electro-Mechanical Impedance (EMI) technique has emerged as a highly sensitive method for detecting incipient damage through the electromechanical coupling characteristics of piezoelectric (PZT) sensors. This study contributes to EMI-based SHM by numerically investigating the combined effects of structural damage and temperature variations on the impedance response of a PZT patch bonded to an aluminum beam.
The methodology relies on three-dimensional finite element modelling performed in ANSYS Multiphysics, incorporating temperature-dependent material properties for both the host structure and the PZT sensor. Several damage scenarios were simulated by introducing cracks of varying depths at a fixed distance from the sensor. Temperature was varied from 25°C to 85°C to evaluate its influence on the electrical impedance signature. Harmonic analyses were conducted over a high-frequency range (18.5–21 kHz) to obtain both the real and imaginary components of the impedance. Damage indices such as Root Mean Square Deviation (RMSD) and Correlation Coefficient Deviation Metric (CCDM) were computed to quantify structural changes.
The results show that increasing temperature produces notable horizontal and vertical shifts in impedance peaks, while increasing crack depth leads to frequency shifts and the emergence of new resonance peaks due to stiffness reduction. Although temperature effects can mask true damage signatures, the application of a cross-correlation-based compensation technique successfully mitigates these distortions, enabling clear distinction between temperature-induced variations and actual structural deterioration.
Overall, the numerical findings confirm that the EMI technique, when combined with adequate temperature compensation strategies ,offers high sensitivity and robustness for reliable, continuous structural health monitoring.
