R. Saveeth1,*, S. Uma Maheswari2
Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 983-1000, 2022, DOI:10.32604/iasc.2022.023455
Abstract In the aerospace industry, composite materials are becoming more common. The presence of a crack in an aircraft makes it weaker and more dangerous, and it can lead to complete fracture and catastrophic failure. To predict the position and depth of a crack, various methods have been developed. For aircraft repair, crack diagnosis is extremely important. Even then, due to uncertainties arising from sources such as environmental conditions, packing, and intrinsic material property changes, accurate diagnosis in real engineering applications remains a challenge. Deep learning (DL) approaches have demonstrated powerful recognition potential in a variety of fields in recent years.… More >
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