Prediction of bead geometry in cold metal transfer welding using back propagation neural network-Reference-Cited by-同舟云学术

Prediction of bead geometry in cold metal transfer welding using back propagation neural network

Published:2016-10-15 Issue:1-4 Volume:93 Page:385-392
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

Pavan Kumar N,Devarajan Praveen K,Arungalai Vendan S,Shanmugam N.

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

http://link.springer.com/article/10.1007/s00170-016-9562-8/fulltext.html

Reference19 articles.

1. Cam G, Dos Santos, J.F, and Kocak M (1997) Laser and electron beam weldability of Al-alloys: literature review. GKSS Report 97/E/25, IIW Document IX-1896-98, GKSS Research Centre, Geesthacht

2. Pickin CG, Williams SW, Lunt M (2011) Characterisation of the cold metal transfer (CMT) process and its application for low dilution cladding. J Materials Processing Techno 211:496–502

3. Senthil Kumar R, Parmer, R.S (1986) Weld bead geometry prediction for pulse MIG welding. In: Proceedings of an International Conference on Trends in Welding Technology, USA, May 18–22: 647–652

4. Srinivasa Rao P (2004) Development of arc rotation mechanism and experimental studies on pulsed GMA welding with and without arc rotation. I.I.T, Kharagpur

5. Srinivasa Rao P, Gupta O.P, Murty, S.S.N (2005) Influence of process parameters on bead geometry in pulsed gas metal arc welding. In: IIW International Congress on Frontiers of Welding Science and Technology, Mumbai

Cited by 29 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction and optimization of tensile properties of 2219-T8 aluminum alloy TIG welding joint by machine learning;Materials & Design;2024-09

2. Effect of Al-Si and Al-Mg filler wires on microstructure and mechanical properties of bead-on-plate weld on AA6061-T6 using CMT welding;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2024-04-01

3. A Machine Learning Approach for Prediction of Surface Temperature of the Weld Region in A-TIG Welding;Transactions of the Indian Institute of Metals;2023-12-17

4. Fuzzy control of backside weld width in cold metal transfer welding of X65 pipeline in the vertical-up position;Welding in the World;2023-12-05

5. Towards a general and numerically efficient deposition model for wire-arc directed energy deposition;Additive Manufacturing;2023-09