Development and Evaluation of a Self-Sensing Kevlar-Carbon Fiber Hybrid Composite for Enhanced Structural Health Monitoring
This research introduces an innovative self-sensing hybrid composite material, skillfully integrating Kevlar and carbon fibers within a cohesive matrix. The study's primary objective is to substantially improve the mechanical strength and decrease the weight of fiber-reinforced polymer (FRP) co...
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Veröffentlicht in: | IEEE sensors journal 2024-11, p.1-1 |
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Hauptverfasser: | , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This research introduces an innovative self-sensing hybrid composite material, skillfully integrating Kevlar and carbon fibers within a cohesive matrix. The study's primary objective is to substantially improve the mechanical strength and decrease the weight of fiber-reinforced polymer (FRP) composites. By strategically employing carbon fibers as conductive channels and Kevlar fibers as an insulating barrier, this study innovatively embeds a capacitive sensing functionality within the composite matrix. This sensor is intricately designed for the real-time, continuous assessment of strain and the preemptive detection of structural integrity issues. The electromechanical attributes of the newly developed composite are meticulously evaluated using sophisticated scanning electron microscopy (SEM) and tensile testing methodologies. These evaluations disclose the material's outstanding ability to detect preliminary damage. Results reveal a direct relationship between the composite's axial stress responses and its sensitivity coefficient, quantified at an approximate value of 1.7. Additionally, the material demonstrates a consistent linear behavior under lateral strains until reaching its failure point, highlighted by remarkably high gauge factors of around -19. The integrated capacitive sensor exhibits exceptional sensitivity, providing invaluable insights into the material's stress-strain dynamics and substantially enhancing its applicability in real-time structural health monitoring (SHM) settings. |
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ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2024.3485231 |