Prediction of Weld Bead Profile Using Neural Networks

In fusion welding process, a monolithic structure is obtained at the weldment between the two pieces to be joined. This monolithic structure called the welded zone has got different shapes, which depend upon the type of welding process and its parameters. The strength of the welded structure depends upon the extent to which the metal penetrates between the joint and the volume of the parent metal that gets melted. The shape of the weldment governs mechanical properties of the structure. The weldment shape is generally represented by bead width, bead height and bead penetration. In this study, two neural network-based approaches have been developed to predict the locus of weld fusion zone.

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