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Failure strength prediction of aluminum spot-welded joints using kernel ridge regression
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Lightweight Structures.
2017 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 91, no 9-12, p. 3717-3725Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer London, 2017. Vol. 91, no 9-12, p. 3717-3725
Keywords [en]
Kernel ridge regression, Resistance spot welding, Failure strength, Truncated Newton, Aluminum alloys
National Category
Manufacturing, Surface and Joining Technology
Identifiers
URN: urn:nbn:se:kth:diva-212608DOI: 10.1007/s00170-017-0070-2ISI: 000406976500067Scopus ID: 2-s2.0-85010733370OAI: oai:DiVA.org:kth-212608DiVA, id: diva2:1135932
Note

QC 20170824

Available from: 2017-08-24 Created: 2017-08-24 Last updated: 2017-08-24Bibliographically approved

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