TY - JOUR AU - Lu, Yao AU - Xing, Yanfeng AU - Li, Xuexing AU - Xu, Sha PY - 2020/07/19 Y2 - 2024/03/29 TI - A new approach of CMT seam welding deformation forecasting based on GA-BPNN JF - Frattura ed Integrità Strutturale JA - Fra&IntStrut VL - 14 IS - 53 SE - Advanced Manufacturing and Processing DO - 10.3221/IGF-ESIS.53.25 UR - https://www.fracturae.com/index.php/fis/article/view/2726 SP - 325-336 AB - <p>Welding deformation affects the quality of the welded parts. In this paper, by introducing improved back propagation neural network (BPNN), a cold metal transfer (CMT) welding deformation prediction model for aluminum-steel hybrid sheets is established. Before applying BPNN, important parameters affecting welding deformation were obtained by orthogonal test and gray relational grade theory. The accuracy of welding deformation prediction of BPNN is improved by genetic algorithm. The results show that compared with the prediction method based on traditional theory, the deformation prediction model based on GA-BPNN has higher accuracy. Predicted results were applied to the aluminum-steel CMT seam welding in the form of inverse deformation, and the deformation of the welded plate was significantly improved.</p> ER -