An efficient crack detection and leakage monitoring in liquid metal pipelines using a novel BRetN and TCK-LSTM techniques
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-20170-6.pdf
Reference36 articles.
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3. Li N, Wang F, Song G (2020) New entropy-based vibro-acoustic modulation method for metal fatigue crack detection: An exploratory study. Measurement 150:107075. https://doi.org/10.1016/j.measurement.2019.107075
4. Seguini M, Khatir S, Boutchicha D et al, (2021) Crack prediction in pipeline using ANN-PSO based on numerical and experimental modal analysis. Smart Structures and Systems 27(3):507–523.https://doi.org/10.12989/sss.2021.27.3.507
5. Kim JJ, Kim AR, Lee SW (2020) Artificial neural network-based automated crack detection and analysis for the inspection of concrete structures. Applied Sciences 10(22):8105.https://doi.org/10.3390/app10228105
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