Description

• Title:
  Local binary pattern defect recognition approach for the friction stir welded AA 1200 and AA 6061-T6 aluminum alloy
• Creator:
  Akshansh Mishra
• Description:
  The research reported in this paper focuses on the application of Local Binary Patterns (LBPs) for surface defects detection. The surface defection detection algorithm for Friction Stir Welded aluminum plates is the key part of the entire surface defect recognition system. Two different grades i.e AA 1200 and AA 6061 plates were similarly joined with the help of Friction Stir Welding process. Python codes for the proposed algorithm were executed on Google Colaboratory platform. The results obtained prove that the Local Binary Patterns method can be used for real-time surface defects detection in Friction Stir Welded joints.
• Object availability:
  free access
• Rights:
  Biblioteka Politechniki Koszalińskiej;
  internet;
  Creative Commons BY 4.0
• Date:
  2020.12.31;
  2020
• Type:
  artykuł w czasopiśmie
• Language:
  English;
  eng
• Format:
  application/pdf
• Publisher:
  Publishing House of the Koszalin University of Technology
• Subject:
  local binary patterns;
  friction stir welding;
  machine learning;
  surface defects
• Data provider:
  Biblioteka Cyfrowa Politechniki Koszalińskiej
• Can I use it?:
  seek permission
• Type:
  image