A new passive vision weld seam tracking method for FSW based on K-means
Author:
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00170-023-12169-4.pdf
Reference25 articles.
1. Mohan DG, Wu C (2021) A review on friction stir welding of steels. Chin J Mech Eng 34:137. https://doi.org/10.1186/s10033-021-00655-3
2. Mishra D, Roy RB, Dutta S, Pal SK, Chakravarty D (2018) A review on sensor based monitoring and control of friction stir welding process and a roadmap to Industry 4.0. J Manuf Process 36:373–397. https://doi.org/10.1016/j.jmapro.2018.10.016
3. Mendes N, Neto P, Simão MA, Loureiro A, Pires JN (2016) A novel friction stir welding robotic platform: welding polymeric materials. Int J Adv Manuf Technol 85:37–46. https://doi.org/10.1007/s00170-014-6024-z
4. Bagheri B, Abdollahzadeh A, Abbasi M, Kokabi AH (2020) Numerical analysis of vibration effect on friction stir welding by smoothed particle hydrodynamics (SPH). Int J Adv Manuf Technol 110:209–228. https://doi.org/10.1007/s00170-020-05839-0
5. Dadaei M, Omidvar H, Bagheri B, Jahazi M, Abbasi M (2014) The effect of SiC/Al2O3 particles used during FSP on mechanical properties of AZ91 magnesium alloy. Int J Mater Res 105:369–374. https://doi.org/10.3139/146.111025
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