Power spectral density moment of having defective 3D printed plastic beams under moving load based on deep learning

Author:

Nguyen Thanh Q.ORCID,Nguyen Nghi N.,Van Tran Xuan

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Reference79 articles.

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2. Abdo, M. B., & Hori, M. (2002). A numerical study of structural damage detection using changes in the rotation of mode shapes. Journal of Structural Engineering, 251(2), 227–239.

3. Ahkami, M., Roesgen, T., Saar, M. O., & Kong, X. Z. (2019). High-resolution temporo-ensemble PIV to resolve pore-scale flow in 3D-printed fractured porous media. Transport in Porous Media, 129, 467–483.

4. Altan, A., Karasu, S., & Bekiros, S. (2019). Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques. Chaos, Solitons & Fractals, 126, 325–336.

5. Bacha, A., Sabry, A. H., & Benhra, J. (2019). Fault diagnosis in the field of additive manufacturing (3D Printing) using Bayesian networks. International Journal of Online & Biomedical Engineering, 15(3), 110–123.

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