Academic Journal
Dynamic Response-Based Bridge Monitoring and Structural Assessment: A Structured Scoping Review and Evidence Inventory.
| Title: | Dynamic Response-Based Bridge Monitoring and Structural Assessment: A Structured Scoping Review and Evidence Inventory. |
|---|---|
| Authors: | Bacha, Muhammad Ziad, Puppio, Mario Lucio, Zucca, Marco, Sassu, Mauro |
| Source: | Infrastructures; Apr2026, Vol. 11 Issue 4, p134, 30p |
| Subject Terms: | Structural health monitoring, Structural dynamics, Machine learning, Structural analysis (Engineering), Digital twin, Live loads, Signal processing, Fault diagnosis |
| Abstract: | Dynamic response measurements support bridge monitoring and structural assessment because they are obtainable under operational loading and are sensitive to changes in stiffness, boundary conditions, and mass distribution. This article presents a structured scoping review of dynamic-response-based bridge monitoring and assessment. It covers damage-sensitive indicators, stiffness/capacity proxy inference, interpretation under operational and extreme loading, sensing with acquisition (contact, and indirect/drive-by), and data processing, machine learning and digital-twin integration for decision support. Evidence was identified through targeted searches in Scopus and The Lens with duplicate resolution in Zotero. The cited studies are compiled into a traceable evidence inventory linked to method families and decision objectives. The synthesis shows that global modal properties enable change screening but are highly confounded by environmental/operational variability. Localization and state characterization typically require denser or higher-fidelity sensing and signal conditioning. Finally, capacity-related inference using calibrated conversion models or machine learning (ML) surrogates remains context-bounded and validation-dependent. This review provides an end-to-end pipeline, evidence-maturity rubric, and conservative failure-mode checks with escalation logic that tie SHM outputs to inspection and analysis rather than direct condition declarations for bridge owners. This review is intentionally scoped and does not claim PRISMA-style comprehensiveness. [ABSTRACT FROM AUTHOR] |
| Copyright of Infrastructures is the property of MDPI 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: Dynamic Response-Based Bridge Monitoring and Structural Assessment: A Structured Scoping Review and Evidence Inventory. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bacha%2C+Muhammad+Ziad%22">Bacha, Muhammad Ziad</searchLink><br /><searchLink fieldCode="AR" term="%22Puppio%2C+Mario+Lucio%22">Puppio, Mario Lucio</searchLink><br /><searchLink fieldCode="AR" term="%22Zucca%2C+Marco%22">Zucca, Marco</searchLink><br /><searchLink fieldCode="AR" term="%22Sassu%2C+Mauro%22">Sassu, Mauro</searchLink> – Name: TitleSource Label: Source Group: Src Data: Infrastructures; Apr2026, Vol. 11 Issue 4, p134, 30p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Structural+health+monitoring%22">Structural health monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+dynamics%22">Structural dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+analysis+%28Engineering%29%22">Structural analysis (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Live+loads%22">Live loads</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Dynamic response measurements support bridge monitoring and structural assessment because they are obtainable under operational loading and are sensitive to changes in stiffness, boundary conditions, and mass distribution. This article presents a structured scoping review of dynamic-response-based bridge monitoring and assessment. It covers damage-sensitive indicators, stiffness/capacity proxy inference, interpretation under operational and extreme loading, sensing with acquisition (contact, and indirect/drive-by), and data processing, machine learning and digital-twin integration for decision support. Evidence was identified through targeted searches in Scopus and The Lens with duplicate resolution in Zotero. The cited studies are compiled into a traceable evidence inventory linked to method families and decision objectives. The synthesis shows that global modal properties enable change screening but are highly confounded by environmental/operational variability. Localization and state characterization typically require denser or higher-fidelity sensing and signal conditioning. Finally, capacity-related inference using calibrated conversion models or machine learning (ML) surrogates remains context-bounded and validation-dependent. This review provides an end-to-end pipeline, evidence-maturity rubric, and conservative failure-mode checks with escalation logic that tie SHM outputs to inspection and analysis rather than direct condition declarations for bridge owners. This review is intentionally scoped and does not claim PRISMA-style comprehensiveness. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Infrastructures is the property of MDPI 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: 10.3390/infrastructures11040134 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 134 Subjects: – SubjectFull: Structural health monitoring Type: general – SubjectFull: Structural dynamics Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Structural analysis (Engineering) Type: general – SubjectFull: Digital twin Type: general – SubjectFull: Live loads Type: general – SubjectFull: Signal processing Type: general – SubjectFull: Fault diagnosis Type: general Titles: – TitleFull: Dynamic Response-Based Bridge Monitoring and Structural Assessment: A Structured Scoping Review and Evidence Inventory. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bacha, Muhammad Ziad – PersonEntity: Name: NameFull: Puppio, Mario Lucio – PersonEntity: Name: NameFull: Zucca, Marco – PersonEntity: Name: NameFull: Sassu, Mauro IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 24123811 Numbering: – Type: volume Value: 11 – Type: issue Value: 4 Titles: – TitleFull: Infrastructures Type: main |
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