Sensitivity Analysis of Electromechanical Impedance Signals for Early Detection of Debonding in Sandwich Face Layers: A Case Study Using SHM Data

Main Article Content

Waleed A Hammood
Salwana Mohamad Asmara
Marshima Mohd Rosli
Idan I. Ghdhban
Ejiro U Osiobe

Abstract

This study investigates the application of sensitivity analysis of electromechanical impedance signals for sandwich composite face layer early debonding detection, in light of several research challenges, including data variability and reliability of the noted signals in response to structural variations. The study makes use of extensive data recorded from SHM systems, combining impedance measurements, structural response data, and debonding characteristics to explore the relationship between sensor output and debonding patterns. The results highlight the usefulness of using sensitivity analysis for pre-debond detection in sandwich composites, as there is a strong relationship between the change in impedance and the integrity of the sandwich composite. Although this approach is particularly relevant to enabling better monitoring strategies in structural health management, we are also aware of the implications of our study in high-impact sectors like healthcare, where composite materials (medical devices, surgical fixtures, etc.) are commonly used. This research has far-reaching implications for the management of large data sets and the development of more reliable diagnostic tools and increased patient safety. This study not only fills knowledge gaps but strengthens the bridges between engineering and healthcare disciplines by encouraging novel techniques in preventative maintenance and health monitoring, promoting a better understanding of electromechanical phenomena in systems that are critical for the health of individuals and society as a whole.


 


 


 


 

Article Details

Section

Articles

How to Cite

Sensitivity Analysis of Electromechanical Impedance Signals for Early Detection of Debonding in Sandwich Face Layers: A Case Study Using SHM Data (W. A. . Hammood, S. M. . Asmara, M. M. . Rosli, I. I. . Ghdhban, & E. U. . Osiobe , Trans.). (2025). Mesopotamian Journal of Civil Engineering, 2025, 1-19. https://doi.org/10.58496/MJCE/2025/001