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YANG Yachao, QUAN Huimin, DENG Linfeng, ZHAO Zhenxing. Prediction method of welding machine parameters based on neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(1): 32-36. DOI: 10.12073/j.hjxb.2018390008
Citation: YANG Yachao, QUAN Huimin, DENG Linfeng, ZHAO Zhenxing. Prediction method of welding machine parameters based on neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(1): 32-36. DOI: 10.12073/j.hjxb.2018390008
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Prediction method of welding machine parameters based on neural network

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  • Received Date: July 10, 2016
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    • Abstract
  • In view of the fact that pulse MIG welding has many parameters and is difficult to adjust, a welding parameter prediction method based on neural network is proposed. This method, having established BP neural network model of welding parameters by adopting LM(levenberg-marquarlt) algorithm, and making full use of the known data to train the network, have realized the prediction of the output parameters in any given welding current state, and then conduct test weld on single and double pulse MIG welding respectively by using the predicted values of welding parameters. The results show that the prediction method of welding parameters based on neural network is of high accuracy, that the welding process is stable, and that the seams can be well-formed, thus achieving a good unified adjustment.
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