An acoustic signal-to-image conversion integrated convolutional neural network model for egg crack detection

Basit Öğe Kaydı
dc.authorid0000-0001-8075-3579
dc.authorid0000-0002-1389-1784
dc.contributor.authorBalci, Z.
dc.contributor.authorYabanova, I.
dc.contributor.authorMert, A.
dc.date.accessioned2026-02-08T15:15:31Z
dc.date.available2026-02-08T15:15:31Z
dc.date.issued2025
dc.departmentBursa Teknik Üniversitesi
dc.description.abstract1. The presence of fractures or cracks in eggshells represent a significant risk in terms of food safety. Bacteria and viruses are likely to enter through these cracks, which increases the risk of food poisoning. Furthermore, deformations in the shell can compromise the integrity of the protective shell, rendering the egg more susceptible to environmental damage and accelerating deterioration.2. In order to mitigate these risks, a convolutional neural network (CNN) integrated into an acoustic signal to image conversion was developed as a crack detection system. Mechanical and electronic sub-systems were designed to generate non-destructive acoustic excitation on the eggshell and capture the resulting sound with a high-sensitivity microphone.3. The recorded 1 x 731-sample signals from 120 intact or cracked eggs were subjected to variational mode decomposition (VMD) to extract intrinsic mode functions (IMF). Subsequently, IMF were converted to greyscale images and classified using the proposed acoustic signal-to-image conversion and the lightweight CNN.4. The proposed model showed the capability (100%) to distinguish between intact and cracked eggs, including invisible micro-cracks.
dc.identifier.doi10.1080/00071668.2025.2549548
dc.identifier.issn0007-1668
dc.identifier.issn1466-1799
dc.identifier.pmid40952330
dc.identifier.scopus2-s2.0-105016808721
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1080/00071668.2025.2549548
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5821
dc.identifier.wosWOS:001572196200001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofBritish Poultry Science
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzWOS_KA_20260207
dc.subjectVariational mode decomposition
dc.subjectdefect detection
dc.subjectacoustic signal
dc.subjectconvolutional neural network
dc.subjecteggshell crack detection
dc.titleAn acoustic signal-to-image conversion integrated convolutional neural network model for egg crack detection
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
PubMed İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu