G.Dhivyasri, M.Manikandan, Dhamodhar Reddy and Koushik P, Department of Electronics and communication Engineering, KPR Institute of Engineering and Technology, India
Chella Babu, Department of Electrical and Electronics, Siddartha Institute of Science and Technology, India
K. Vinoth Kumar, EMC Calibration Engineer, OSRAM Continental Pvt.Ltd., India
Online First : 30 December 2020
Publisher Name : IJAICT India Publications, India.
Print ISBN : 978-81-950008-0-7
Online ISBN : 978-81-950008-1-4
Page :250-255
Abstract
In order to achieve the desired bead geometry in a welding operation it is of prime importance to select suitable process parameters. In this research, pulsed MIG welding of 316L austenitic stainless steel is perforated and its bead geometry is studied, such as penetration depth bead width and height of reinforcement. The optimization approach based on the Genetic Algorithm (GA) is implemented to ensure the optimal combination of process variables and bead geometry. Regression model are initially generated by using experimental data. GA is then generated to optimize the parameters of the method and bead geometry parameters by minimizing the objective function based on the least square error. Pulsed MIG welded parameters was experimentally tested by microscopic analysis and EDAX analysis for three sample sets. The finding suggest that expected and experimental values are close in agreement. Finally, the effect of the welding current on the elemental composition is seen. The research shows that in the GA based method, the rate of convergence is faster.
Keywords
Pulsed MIG, DOP, BW, RH, GA
Cite this article
G.Dhivyasri, M.Manikandan, Dhamodhar Reddy, Koushik P, Chella Babu and K. Vinoth Kumar, “Evolutionary Algorithm On Cold Metal Transfer Process For Feature Extraction”, Innovations in Information and Communication Technology, pp. 250-255, December 2020.
Copyright
© 2020 G.Dhivyasri, M.Manikandan, Dhamodhar Reddy, Koushik P, Chella Babu and K. Vinoth Kumar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
