Skilled human welder intelligence modeling and control: Part 1 - Modeling

Y. K. Liu, Y. M. Zhang, L. Kvidahl

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Skilled human welders' experiences and skills are critical for producing quality welds with the manual gas tungsten arc welding (GTAW) process. In this study, a skilled human welder's response to 3D weld pool surface was modeled. To this end, an innovative vision system was utilized to measure in real time the specular 3D weld pool surface under strong arc interference in the GTAW process. Experiments were designed to produce random changes in the welding speed and voltage, resulting in fluctuations in the weld pool surface. A skilled human welder made adjustments on the welding current based on his/her observation of the weld pool and these adjustments were then recorded. Adaptive neuro-fuzzy inference system (ANFIS) was proposed to correlate a skilled human welder response to the fluctuating 3D weld pool surface and previous welding current adjustment made by the welder. It was found that the proposed ANFIS model can model the human welder intelligence with acceptable accuracy. The resultant model will be compared with the model derived from a novice welder, analyzed, and utilized to control the GTAW process to achieve consistent complete joint penetration under different initial current and various disturbances in a future study.

Original languageEnglish
Pages (from-to)46s-52s
JournalWelding Journal
Volume93
Issue number2
StatePublished - Feb 2014

Keywords

  • ANFIS modeling
  • GTAW
  • Machine vision
  • Skilled welder intelligence
  • Weld pool

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering
  • Metals and Alloys

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