Fatigue behavior and vibration-based integrity management of advanced composite structures: A comprehensive review

Journal of Low Frequency Noise, Vibration and Active Control

卷:45

Reviews

Mustafa Akbulut¹  Ibrahim T. Teke²  Ahmet H. Ertas³ 

[1] Department of Mechanical Engineering, Faculty of Engineering, , Istanbul, Türkiye

[2] Department of Mechanical Engineering, Faculty of Engineering & Natural Sciences, , Bursa, Türkiye

[3] Department of Industrial Design, Faculty of Engineering and Natural Sciences, , Istanbul, Türkiye

关键词: composite laminates;    fatigue damage;    vibration-based structural health monitoring;    modal parameters;    stiffness degradation;    Operational Modal Analysis (OMA);    Continuum Damage Mechanics (CDM);    delamination;    physics-informed machine learning;    digital twin;    environmental effects;   

DOI  :  10.1177/14613484261447237

 received in 2025-10-30, accepted in 2026-04-14,  发布年份 2026

来源: Sage Journals

【 摘 要 】

Composite materials are widely used in aerospace, automotive, and marine engineering because of their high strength-to-weight ratio and design flexibility. However, their long-term reliability is limited by fatigue damage, which develops gradually through matrix cracking, delamination, and fiber fracture under cyclic loading. Conventional fatigue-life prediction methods often fail to capture early degradation and typically require extensive experimental calibration. Vibration-based Structural Health Monitoring (SHM) offers a non-destructive alternative by exploiting the direct relationship between stiffness degradation and changes in dynamic properties such as natural frequencies, damping ratios, and mode shapes. This review synthesizes current research linking vibration response to fatigue damage in composite structures. Experimental methods, sensing technologies, and computational modeling approaches are examined within a unified framework. Particular attention is given to sandwich and auxetic configurations, environmental influences, and design optimization for improved fatigue resistance. The study also discusses emerging data-driven paradigms, including physics-guided machine learning and digital-twin concepts, which enable predictive maintenance rather than post-damage detection. By integrating mechanics-based understanding with monitoring and data analytics, this review provides a structured perspective on vibration-based integrity assessment and outlines research directions toward reliable in-service monitoring and extended operational life of advanced composite structures.

【 授权许可】

CC BY-NC   
© The Author(s) 2026