Intelligent vibration-based structural health monitoring systems: Methodological advances and challenges

Khodadoost, S; Nouhi, B; Talatahari, S; Sareh, P

Intelligent vibration-based structural health monitoring systems: Methodological advances and challenges

Khodadoost, S Nouhi, B Talatahari, S Sareh, P

Permalink

Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Sensors and Actuators A Physical, 2025, 394, pp. 116886
Issue Date:: 2025-11

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (11.06 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Khodadoost, S
dc.contributor.author	Nouhi, B
dc.contributor.author	Talatahari, S
dc.contributor.author	Sareh, P
dc.date.accessioned	2026-05-14T05:19:32Z
dc.date.available	2026-05-14T05:19:32Z
dc.date.issued	2025-11
dc.identifier.citation	Sensors and Actuators A Physical, 2025, 394, pp. 116886
dc.identifier.issn	0924-4247
dc.identifier.uri	http://hdl.handle.net/10453/194988
dc.description.abstract	Ensuring the safety and longevity of engineering structures requires the development of robust and efficient damage detection strategies. Traditional structural health monitoring (SHM) methods, which often rely on time-consuming and potentially disruptive direct assessments, are increasingly being replaced by more intelligent and effective vibration-based SHM techniques. These advancements are primarily driven by improvements in sensor technology, computational power, and signal processing algorithms. This paper investigates the latest developments in intelligent vibration-based SHM systems, a rapidly evolving field that leverages structural vibration analysis for highly sensitive damage detection. It specifically explores the integration of optimization algorithms and artificial intelligence techniques to enhance the precision, efficiency, and real-time capabilities of damage detection systems. It also provides a comprehensive overview of state-of-the-art vibration-based methods, including modal analysis, frequency response functions, and signal processing techniques. Additionally, it highlights the role of optimization algorithms, machine learning, and innovative hybrid approaches in shaping the future of SHM.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Sensors and Actuators A Physical
dc.relation.isbasedon	10.1016/j.sna.2025.116886
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0906 Electrical and Electronic Engineering, 0912 Materials Engineering, 0913 Mechanical Engineering
dc.subject.classification	Nanoscience & Nanotechnology
dc.subject.classification	4008 Electrical engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.subject.classification	4017 Mechanical engineering
dc.title	Intelligent vibration-based structural health monitoring systems: Methodological advances and challenges
dc.type	Journal Article
utslib.citation.volume	394
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	0912 Materials Engineering
utslib.for	0913 Mechanical Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/Engineering and IT Related HDR Students
utslib.copyright.status	open_access	*
pubs.consider-herdc	true
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2026-05-14T05:19:30Z
pubs.publication-status	Published
pubs.volume	394

Abstract:

Ensuring the safety and longevity of engineering structures requires the development of robust and efficient damage detection strategies. Traditional structural health monitoring (SHM) methods, which often rely on time-consuming and potentially disruptive direct assessments, are increasingly being replaced by more intelligent and effective vibration-based SHM techniques. These advancements are primarily driven by improvements in sensor technology, computational power, and signal processing algorithms. This paper investigates the latest developments in intelligent vibration-based SHM systems, a rapidly evolving field that leverages structural vibration analysis for highly sensitive damage detection. It specifically explores the integration of optimization algorithms and artificial intelligence techniques to enhance the precision, efficiency, and real-time capabilities of damage detection systems. It also provides a comprehensive overview of state-of-the-art vibration-based methods, including modal analysis, frequency response functions, and signal processing techniques. Additionally, it highlights the role of optimization algorithms, machine learning, and innovative hybrid approaches in shaping the future of SHM.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/194988