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• W2050621858 abstract "An experimental investigation has been carried out to determine the applicability of an induction heating process with a travelling induction coil for the rectification of angular welding distortion. The results obtained from experimentation have been used to create artificial neural network (ANN) models with the ability to predict the weld-induced distortion and the distortion rectification achieved using a travelling induction coil. The experimental results have shown the ability to reduce the angular distortion for 8- and 10-mm thick DH36 steel plates and effectively eliminate the distortion on 6-mm thick plates. Results for 6-mm plates also show the existence of a critical induction coil travel speed, at which maximum corrective bending occurs. ANNs have demonstrated the ability to predict the final distortion of the plate both after welding and induction heating. The models have also been used as a tool to determine the optimum speed to minimise the resulting distortion of a steel plate after being subjected to both welding and induction heating processes." @default.
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• W2050621858 date "2013-01-17" @default.
• W2050621858 modified "2023-10-16" @default.
• W2050621858 title "Artificial neural network prediction of weld distortion rectification using a travelling induction coil" @default.
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• W2050621858 doi "https://doi.org/10.1007/s00170-012-4713-z" @default.
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