Crack Identification in Pipe Using Improved Artificial Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-4835-0_2
Reference17 articles.
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2. Gillich GR, Maia MM, Wahab MA, Pop MV (2021) Damage detection on a beam with multiple cracks: a simplified method based on relative frequency shifts. https://doi.org/10.20944/preprints202107.0240.v1
3. Seguini M, Boutchicha D, Khatir S, Nedjar D, Waheb MA (2022) Crack prediction in beam-like structure using ANN based on frequency analysis. Frattura ed Integrità Strutturale 59:18–34. https://doi.org/10.3221/IGF-ESIS.59.02
4. Zhou YL, Maia NM, Sampaio RP, Wahab MA (2017) Structural damage detection using transmissibility together with hierarchical clustering analysis and similarity measure. Struct Health Monit 16:711–731. https://doi.org/10.1177/1475921716680849
5. Zhou YL, Maia NM, Abdel Wahab M (2018) Damage detection using transmissibility compressed by principal component analysis enhanced with distance measure. J Vib Control 24:2001–2019. https://doi.org/10.1177/1077546316674544
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