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Determination of Weld Nugget Size Using an Inverse Engineering Technique

Journal Article
ISSN: 1946-3995, e-ISSN: 1946-4002
Published April 08, 2013 by SAE International in United States
Determination of Weld Nugget Size Using an Inverse Engineering Technique
Citation: Gu, R., Yang, L., Lev, L., Harmon, G. et al., "Determination of Weld Nugget Size Using an Inverse Engineering Technique," SAE Int. J. Passeng. Cars - Mech. Syst. 6(2):937-943, 2013,
Language: English


In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds.
There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6]. In a forward problem, we are provided with known material model, well-defined boundary conditions, and specific loading conditions - mechanical as well as thermal. For an ill-posed problem [7, 8], some of the known settings may be absent and a set of experimental data is made available for solving the problem. The objective of this study is to investigate the feasibility of an inverse problem technique to determining the weld nugget size using a finite element scheme incorporating experimental measurements on the surface of the weld coupons. In the technique, a mathematical model is formulated to solve the ill-posed inverse problem in which the solution sought is required to satisfy both the experimental measurement and the theoretical foundation of the problem. To demonstrate the efficiency and accuracy of the numerical scheme, several two-dimensional examples are presented. Sensitivity to the solution algorithm from the experimental data is also discussed.