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Classification of Welding Defects in Radiographic Images Using an Adaptive-Network-Based Fuzzy System

  • Rafael Vilar
  • Juan Zapata
  • Ramón Ruiz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6687)

Abstract

In this paper, we describe an automatic system of radiographic inspection of welding. An important stage in the construction of this system is the classification of defects. In this stage, an adaptive-network-based fuzzy inference system (ANFIS) for weld defect classification was used. The results was compared with the aim to know the features that allow the best classification. The correlation coefficients were determined obtaining a minimum value of 0.84. The accuracy or the proportion of the total number of predictions that were correct was determined obtaining a value of 82.6%.

Keywords

Membership Function Fuzzy Inference System Radiographic Image Weld Region Welding Defect 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rafael Vilar
    • 1
  • Juan Zapata
    • 2
  • Ramón Ruiz
    • 2
  1. 1.Departamento de Estructuras y ConstrucciónUniversidad Politécnica de CartagenaCartagenaSpain
  2. 2.Departamento de Electrónica, Tecnología de Computadores y ProyectosUniversidad Politécnica de CartagenaCartagenaSpain

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