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. |
|---|---|
| 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] |
| Copyright of Journal of Nondestructive Evaluation is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Acoustic Emission-Based Assessment of Damage Evolution in Bridge Systems: Methods, Indicators, and Advances in Structural Mechanics. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kudus%2C+Sakhiah+Abdul%22">Kudus, Sakhiah Abdul</searchLink><br /><searchLink fieldCode="AR" term="%22Misnan%2C+Mohamad+Farid%22">Misnan, Mohamad Farid</searchLink><br /><searchLink fieldCode="AR" term="%22Muhammad%2C+Hussein%22">Muhammad, Hussein</searchLink><br /><searchLink fieldCode="AR" term="%22Sawahli%2C+Abdulrahman+Mubarak+Salem%22">Sawahli, Abdulrahman Mubarak Salem</searchLink><br /><searchLink fieldCode="AR" term="%22Ahmad%2C+Zakiah%22">Ahmad, Zakiah</searchLink><br /><searchLink fieldCode="AR" term="%22Shahid%2C+Khairul+Anuar%22">Shahid, Khairul Anuar</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of Nondestructive Evaluation; Sep2026, Vol. 45 Issue 3, p1-52, 52p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Acoustic+emission%22">Acoustic emission</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+health+monitoring%22">Structural health monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Fatigue+cracks%22">Fatigue cracks</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Corrosion+%26+anti-corrosives%22">Corrosion & anti-corrosives</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of Nondestructive Evaluation is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10921-026-01388-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 52 StartPage: 1 Subjects: – SubjectFull: Acoustic emission Type: general – SubjectFull: Structural health monitoring Type: general – SubjectFull: Fatigue cracks Type: general – SubjectFull: Signal processing Type: general – SubjectFull: Digital twin Type: general – SubjectFull: Corrosion & anti-corrosives Type: general – SubjectFull: Machine learning Type: general Titles: – TitleFull: Acoustic Emission-Based Assessment of Damage Evolution in Bridge Systems: Methods, Indicators, and Advances in Structural Mechanics. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kudus, Sakhiah Abdul – PersonEntity: Name: NameFull: Misnan, Mohamad Farid – PersonEntity: Name: NameFull: Muhammad, Hussein – PersonEntity: Name: NameFull: Sawahli, Abdulrahman Mubarak Salem – PersonEntity: Name: NameFull: Ahmad, Zakiah – PersonEntity: Name: NameFull: Shahid, Khairul Anuar IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 01959298 Numbering: – Type: volume Value: 45 – Type: issue Value: 3 Titles: – TitleFull: Journal of Nondestructive Evaluation Type: main |
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