Failure strength prediction of aluminum spot-welded joints using kernel ridge regression

Failure strength prediction of aluminum spot-welded joints using kernel ridge regression The current paper presents an alternative method for failure strength prediction of spot-welded joints in aluminum, based on nonlinear regression analysis, namely, the kernel ridge regression method. Welding parameters such as electrode force, welding current, and welding time are studied in the experimental investigation to measure their effects on the nugget size and failure strength of the resistance spot welds. Coupons are manufactured and tensile tested and the results show that the welding current and time have the largest effect on the nugget size and the failure strength. The results of this study are compared to those of the least squares method and they indicate that the truncated-regularized kernel ridge regression algorithm significantly improves the coefficient of determination and reduces the mean squared error. The International Journal of Advanced Manufacturing Technology Springer Journals

Failure strength prediction of aluminum spot-welded joints using kernel ridge regression

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Springer London
Copyright © 2017 by Springer-Verlag London
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
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