Numerical Analysis of Crack Path Effects on the Vibration Behaviour of Aluminium Alloy Beams and Its Identification via Artificial Neural Networks

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dc.authorid0000-0001-9028-1288
dc.contributor.authorKati, Hilal Doganay
dc.contributor.authorBuhari, Jamilu
dc.contributor.authorFrancese, Arturo
dc.contributor.authorHe, Feiyang
dc.contributor.authorKhan, Muhammad
dc.date.accessioned2026-02-08T15:16:02Z
dc.date.available2026-02-08T15:16:02Z
dc.date.issued2025
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractUnderstanding and predicting the behaviour of fatigue cracks are essential for ensuring safety, optimising maintenance strategies, and extending the lifespan of critical components in industries such as aerospace, automotive, civil engineering and energy. Traditional methods using vibration-based dynamic responses have provided effective tools for crack detection but often fail to predict crack propagation paths accurately. This study focuses on identifying crack propagation paths in an aluminium alloy 2024-T42 cantilever beam using dynamic response through numerical simulations and artificial neural networks (ANNs). A unified damping ratio of the specimens was measured using an ICP (R) accelerometer vibration sensor for the numerical simulation. Through systematic investigation of 46 crack paths of varying depths and orientations, it was observed that the crack propagation path significantly influenced the beam's natural frequencies and resonance amplitudes. The results indicated a decreasing frequency trend and an increasing amplitude trend as the propagation angle changed from vertical to inclined. A similar trend was observed when the crack path changed from a predominantly vertical orientation to a more complex path with varying angles. Using ANNs, a model was developed to predict natural frequencies and amplitudes from the given crack paths, achieving a high accuracy with a mean absolute percentage error of 1.564%.
dc.identifier.doi10.3390/s25030838
dc.identifier.issn1424-8220
dc.identifier.issue3
dc.identifier.pmid39943477
dc.identifier.scopus2-s2.0-85217709533
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/s25030838
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6077
dc.identifier.volume25
dc.identifier.wosWOS:001419651500001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofSensors
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzWOS_KA_20260207
dc.subjectcrack identification
dc.subjectcrack path
dc.subjectnatural frequency and amplitude
dc.subjectartificial neural networks (ANNs)
dc.titleNumerical Analysis of Crack Path Effects on the Vibration Behaviour of Aluminium Alloy Beams and Its Identification via Artificial Neural Networks
dc.typeArticle

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