Application of Machine Learning and Deep Learning Techniques for Corrosion and Cracks Detection in Nuclear Power Plants: A Review
Author:
Funder
King Fahd University of Petroleum and Minerals
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13369-024-09388-6.pdf
Reference128 articles.
1. Speller, F.N.: Corrosion. Mc Graw- Hill Book, Company Inc, New York (1951)
2. Fernandes, J.S.; Montemor, F.: Corrosion. In: Clara Gonçalves, M.; Margarido, F. (Eds.) Materials for Construction and Civil Engineering: Science, Processing, and Design, pp. 679–716. Springer International Publishing, Cham (2015). https://doi.org/10.1007/978-3-319-08236-3_15
3. Lee, J.-H.; Lee, S.-J.: Application of laser-generated guided wave for evaluation of corrosion in carbon steel pipe. NDT and E Int. 42(3), 222–227 (2009). https://doi.org/10.1016/j.ndteint.2008.09.011
4. Cattant, F.; Crusset, D.; Féron, D.: Corrosion issues in nuclear industry today. Mater. Today 11(10), 32–37 (2008). https://doi.org/10.1016/S1369-7021(08)70205-0
5. Huthwaite, P.; Ribichini, R.; Cawley, P.; Lowe, M.J.S.: Mode selection for corrosion detection in pipes and vessels via guided wave tomography. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 60(6), 1165–1177 (2013). https://doi.org/10.1109/TUFFC.2013.2679
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