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Discrete Wavelet Transformation Approach for Surface Defects Detection in Friction Stir Welded Joints Cover

Discrete Wavelet Transformation Approach for Surface Defects Detection in Friction Stir Welded Joints

By: Akshansh Mishra  
Open Access
|Jul 2021

References

  1. [1] Mishra, R.S. and Ma, Z.Y. (2005). Friction stir welding and processing. Materials Science and Engineering: R: Reports, 50(1-2), pp.1-78. 10.1016/j.mser.2005.07.001.10.1016/j.mser.2005.07.001
  2. [2] Thomas, W.M. and Nicholas, E.D. (1997). Friction stir welding for the transportation industries. Materials & Design, 18(4-6), pp.269-273. 10.1016/s0261-3069(97)00062-9.10.1016/S0261-3069(97)00062-9
  3. [3] Lohwasser, D. and Chen, Z. eds. (2009). Friction stir welding: From basics to applications. Elsevier.
  4. [4] Akinlabi, E.T. and Mahamood, R.M. (2020). Introduction to Friction Welding, Friction Stir Welding and Friction Stir Processing. In: Solid-State Welding: Friction and Friction Stir Welding Processes (pp. 1-12). Springer, Cham.10.1007/978-3-030-37015-2
  5. [5] Kolokas, N., Vafeiadis, T., Ioannidis, D. and Tzovaras, D. (2020). Fault Prognostics in Industrial Domains using Unsupervised Machine Learning Classifiers. Simulation Modelling Practice and Theory, 103, p.102109. 10.1016/j.simpat.2020.10210910.1016/j.simpat.2020.102109
  6. [6] Aimiyekagbon, O.K., Bender, A. and Sextro, W. (2020). Evaluation of time series forecasting approaches for the reliable crack length prediction of riveted aluminium plates given insufficient data. In Proceedings of the European Conference of the PHM Society, 5(1), pp. 1-11. Available at: www.phmpapers.org/index.php/pheme/issue/view/4
  7. [7] Mongan, P.G., Hinchy, E.P., O’Dowd, N.P. and McCarthy, C.T., 2020. Optimisation of Ultrasonically Welded Joints through Machine Learning. Procedia CIRP, 93, pp.527-531. 10.1016/j.procir.2020.04.060.10.1016/j.procir.2020.04.060
  8. [8] Dutt A.K., Sindhuja K., Reddy S.V.N., Kumar P. (2021). Application of Artificial Neural Network to Friction Stir Welding Process of AA7050 Aluminum Alloy. In: Arockiarajan A., Duraiselvam M., Raju R. (eds) Advances in Industrial Automation and Smart Manufacturing. Lecture Notes in Mechanical Engineering. Springer, Singapore. 10.1007/978-981-15-4739-3_34.
  9. [9] Hartl, R., Hansjakob, J. & Zaeh, M.F. (2020). Improving the surface quality of friction stir welds using reinforcement learning and Bayesian optimization. The International Journal of Advanced Manufacturing Technology, 110, pp. 3145-3167. 10.1007/s00170-020-05696-x.10.1007/s00170-020-05696-x
  10. [10] Hossam Selim, Fernando Piñal Moctezuma, Miguel Delgado Prieto, José Francisco Trull, Luis Romeral Martínez and Crina Cojocaru (2019). Wavelet Transform Applied to Internal Defect Detection by Means of Laser Ultrasound, Wavelet Transform and Complexity, Dumitru Baleanu, IntechOpen, 10.5772/intechopen.84964. Available from: https://www.intechopen.com/books/wavelet-transform-and-complexity/wavelet-transform-applied-to-internal-defect-detection-by-means-of-laser-ultrasound10.5772/intechopen.84964
  11. [11] Vermaak, H., Nsengiyumva, P. and Luwes, N. (2016). Using the dual-tree complex wavelet transform for improved fabric defect detection. Journal of Sensors, 2016. 10.1155/2016/9794723.10.1155/2016/9794723
  12. [12] Knitter-Piątkowska, A., Guminiak, M.J., Przychodzki, M. (2016). Application of Discrete Wavelet Transformation to Defect Detection in Truss Structures with Rigidly Connected Bars. Engineering Transactions, 64(2,) pp. 157-170. ISSN 2450-8071. Available at: http://www.entra.put.poznan.pl/index.php/et/article/view/319. Date accessed: 01 Nov. 2020.
DOI: https://doi.org/10.2478/fas-2020-0003 | Journal eISSN: 2300-7591 | Journal ISSN: 2081-7738
Language: English
Page range: 27 - 35
Published on: Jul 23, 2021
Published by: ŁUKASIEWICZ RESEARCH NETWORK – INSTITUTE OF AVIATION
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2021 Akshansh Mishra, published by ŁUKASIEWICZ RESEARCH NETWORK – INSTITUTE OF AVIATION
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.