Friction stir welding of 2024 aluminum alloy: Study of major parameters and threading feature on probe

2017 ◽  
Vol 31 (11) ◽  
pp. 5435-5445 ◽  
Author(s):  
Sarah Gholam Nejad ◽  
Mehdi Yektapour ◽  
Arash Akbarifard
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
2024 Aluminum Alloy ◽  
Friction Stir

Defects and tensile properties of 6013 aluminum alloy T-joints by friction stir welding

2014 ◽  
Vol 57 ◽  
pp. 146-155 ◽  
Author(s):  
Yong Zhao ◽  
Lilong Zhou ◽  
Qingzhao Wang ◽  
Keng Yan ◽  
Jiasheng Zou
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Tensile Properties ◽  
T Joints ◽  
Friction Stir

scholarly journals Study on Quality Prediction of 2219 Aluminum Alloy Friction Stir Welding Based on Real-Time Temperature Signal

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3496
Author(s):  
Haijun Wang ◽  
Diqiu He ◽  
Mingjian Liao ◽  
Peng Liu ◽  
Ruilin Lai
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Prediction Model ◽  
Real Time ◽  
Support Vector ◽  
Weld Quality ◽  
Prediction Ability ◽  
Friction Stir ◽  
Temperature Signal ◽  
2219 Aluminum Alloy

The online prediction of friction stir welding quality is an important part of intelligent welding. In this paper, a new method for the online evaluation of weld quality is proposed, which takes the real-time temperature signal as the main research variable. We conducted a welding experiment with 2219 aluminum alloy of 6 mm thickness. The temperature signal is decomposed into components of different frequency bands by wavelet packet method and the energy of component signals is used as the characteristic parameter to evaluate the weld quality. A prediction model of weld performance based on least squares support vector machine and genetic algorithm was established. The experimental results showed that, when welding defects are caused by a sudden perturbation during welding, the amplitude of the temperature signal near the tool rotation frequency will change significantly. When improper process parameters are used, the frequency band component of the temperature signal in the range of 0~11 Hz increases significantly, and the statistical mean value of the temperature signal will also be different. The accuracy of the prediction model reached 90.6%, and the AUC value was 0.939, which reflects the good prediction ability of the model.

Enhanced aluminum alloy-polymer friction stir welding joints by introducing micro-textures

2021 ◽  
pp. 129872
Author(s):  
Wenquan Wang ◽  
Suyu Wang ◽  
Xinge Zhang ◽  
Yuxin Xu ◽  
Yingtao Tian ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Friction Stir ◽  
Polymer Friction ◽  
Welding Joints

Dissimilar aluminum alloy joint strength is effected by heat addition in friction stir welding (FSW)

2021 ◽  
Author(s):  
Sharda Pratap Shrivas ◽  
G.K. Agrawal ◽  
Shubhrata Nagpal ◽  
Amit Kumar Vishvakarma ◽  
Ashish Kumar Khandelwal
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Joint Strength ◽  
Friction Stir ◽  
Heat Addition

Dimensional Analysis of Thermal Fields Surrounding Friction Stir Welding Process

2014 ◽  
Author(s):  
Lewis N. Payton ◽  
Vishnu Vardhan Chandrasekaran ◽  
Wesley S. Hunko
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Welding Process ◽  
Temperature Fields ◽  
Analytical Comparison ◽  
Friction Stir ◽  
Thermal Fields ◽  
Designed Experiment ◽  
Pi Theorem ◽  
Alloy 6061

A dimensionless correlation is developed based on Buckingham’s Pi-Theorem to estimate the temperature fields generated by the movement of a tool during the Friction Stir Welding of an aluminum alloy (6061-T6). Symmetrical thermocouple measurements are taken during a statistically designed experiment using different factor levels (RPM, Traverse, etc). Analytical comparison (using multivariate ANOVA) validates the predicted dimensionless correlation including the often-reported difference between the advancing versus retreating side of the Friction Stir Tool.

scholarly journals Stress corrosion behavior of friction stir welding joint of 7N01 aluminum alloy

2021 ◽  
Vol 15 ◽  
pp. 1130-1144
Author(s):  
Yuzhe Pan ◽  
Yu Wang ◽  
Fuqiang Guo ◽  
Tiehao Zhang ◽  
Kenji Matsuda ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Friction Stir Welding ◽  
Stress Corrosion ◽  
Corrosion Behavior ◽  
Friction Stir ◽  
Welding Joint
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