Advanced Sensors and Sensing Systems for Structural Health Monitoring in Aerospace Composites

This review examines the state‐of‐the‐art sensors and sensing technologies employed for structural health monitoring (SHM) in aerospace composites, highlighting the shift from conventional nondestructive evaluation techniques to real‐time monitoring systems. The review discusses the challenges associated with composite materials, such as their anisotropic nature and susceptibility to invisible damage, and how these challenges have driven the improvement of SHM techniques. Fiber‐optic sensors, including interferometric, distributed, and grating‐based sensors, are analyzed for their high sensitivity and multiplexing capabilities, making them suitable for distributed sensing applications. Piezoelectric sensors are evaluated for their effectiveness in both active and passive damage detection methods. At the same time, piezoresistive self‐sensing systems are explored for their potential to integrate sensing directly into composite materials. The review also addresses the challenges encountered in implementing SHM systems. It suggests solutions like protective coatings, advanced data processing algorithms, and modular system design to overcome these challenges. In conclusion, this review provides a comprehensive overview of the current SHM technologies for aerospace composites, underscoring the need for sustained research and development to improve sensor technology, expand data processing capabilities, and ensure seamless integration with aircraft systems, thus contributing to the safety and efficiency of aerospace operations.

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Publication Details

Journal
Advanced Engineering Materials
Published
2024-10-04
DOI
https://doi.org/10.1002/adem.202401745
Citations
29
Primary Topic
Smart Materials for Construction
Type
article
Field-Weighted Citation Impact
3.86

Funders

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article

Advanced Sensors and Sensing Systems for Structural Health Monitoring in Aerospace Composites

Jakub Javořík, Soňa Rusnáková, Milan Žaludek, Raphael Olabanji Ogunleye et al.
29 citations
Advanced Engineering Materials
Smart Materials for Construction
3.86
article

Advanced Sensors and Sensing Systems for Structural Health Monitoring in Aerospace Composites

Jakub Javořík, Soňa Rusnáková, Milan Žaludek, Raphael Olabanji Ogunleye, Barbora Kotlánová
article en
29 citations

Abstract

This review examines the state‐of‐the‐art sensors and sensing technologies employed for structural health monitoring (SHM) in aerospace composites, highlighting the shift from conventional nondestructive evaluation techniques to real‐time monitoring systems. The review discusses the challenges associated with composite materials, such as their anisotropic nature and susceptibility to invisible damage, and how these challenges have driven the improvement of SHM techniques. Fiber‐optic sensors, including interferometric, distributed, and grating‐based sensors, are analyzed for their high sensitivity and multiplexing capabilities, making them suitable for distributed sensing applications. Piezoelectric sensors are evaluated for their effectiveness in both active and passive damage detection methods. At the same time, piezoresistive self‐sensing systems are explored for their potential to integrate sensing directly into composite materials. The review also addresses the challenges encountered in implementing SHM systems. It suggests solutions like protective coatings, advanced data processing algorithms, and modular system design to overcome these challenges. In conclusion, this review provides a comprehensive overview of the current SHM technologies for aerospace composites, underscoring the need for sustained research and development to improve sensor technology, expand data processing capabilities, and ensure seamless integration with aircraft systems, thus contributing to the safety and efficiency of aerospace operations.

Advanced Engineering MaterialsVol. 26(22)
Tomas Bata University in Zlín (CZ)
Tomas Bata University in Zlin
Openalex Percentile: Top 5%
Smart Materials for Construction
3.86
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