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Prediction of gas metal arc welding parameters based on artificial neural networks

โœ Scribed by Hakan Ates

Publisher
Elsevier Science
Year
2007
Weight
187 KB
Volume
28
Category
Article
ISSN
0261-3069

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โœฆ Synopsis

This paper presents a novel technique based on artificial neural networks (ANNs) for prediction of gas metal arc welding parameters. Input parameters of the model consist of gas mixtures, whereas, outputs of the ANN model include mechanical properties such as tensile strength, impact strength, elongation and weld metal hardness, respectively. ANN controller was trained with the extended delta-bardelta learning algorithm. The measured and calculated data were simulated by a computer program. The results showed that the outcomes of the calculation were in good agreement with the measured data, indicating that the novel technique presented in this work shows the good performance of the ANN model.

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