Academic Journal
Acoustic Emission-Based Assessment of Damage Evolution in Bridge Systems: Methods, Indicators, and Advances in Structural Mechanics.
| Title: | Acoustic Emission-Based Assessment of Damage Evolution in Bridge Systems: Methods, Indicators, and Advances in Structural Mechanics. |
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| Authors: | Kudus, Sakhiah Abdul, Misnan, Mohamad Farid, Muhammad, Hussein, Sawahli, Abdulrahman Mubarak Salem, Ahmad, Zakiah, Shahid, Khairul Anuar |
| Source: | Journal of Nondestructive Evaluation; Sep2026, Vol. 45 Issue 3, p1-52, 52p |
| Subject Terms: | Acoustic emission, Structural health monitoring, Fatigue cracks, Signal processing, Digital twin, Corrosion & anti-corrosives, Machine learning |
| Abstract: | Bridges are essential infrastructure and require reliable monitoring to ensure public safety and structural resilience. This review critically examines research published from 2015 to 2026 on acoustic emission (AE)-based bridge monitoring and clarifies key methods, indicators, and future research directions in the field. Using a systematic review of 40 peer-reviewed articles and PRISMA-based screening, the study highlights the growing effectiveness of AE techniques in detecting and characterizing structural damage, including fatigue, shear cracking, corrosion, and tendon rupture, in critical bridge components, such as cables, tendons, decks, and girders. However, in the provided evidence base that focuses on bridges, discussions of corrosion applications are cited even less than those on fatigue/cracking, tendon rupture diagnostics, and, as such, corrosion conclusions are framed as a research gap rather than an underdeveloped comparative theme. Core AE indicators, b-value, RA–AF analysis, signal energy, and peak frequency, are consistently linked with specific damage mechanisms, supporting early diagnosis and targeted maintenance. The adoption of advanced signal processing, machine learning, and hybrid sensor networks has the potential to enhance the accuracy and real-time capabilities of these systems. Nevertheless, challenges remain regarding sensor placement, environmental noise, signal attenuation, and a lack of standardized interpretation across different bridge materials. This review emphasizes the need for standardized protocols, open-access AE datasets, and cross-disciplinary research to advance system reliability and scalability. Embedding AE monitoring within digital twin frameworks and asset management strategies can further enable proactive maintenance and infrastructure resilience. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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