© 2009

Intelligentized Methodology for Arc Welding Dynamical Processes


  • Presents Intelligent Technologies for Arc Welding Dynamical Process

  • Useful for researchers, practitioners, as well as students


Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 29)

Table of contents

  1. Front Matter
    Pages I-XXIII
  2. Shan-Ben Chen, Jing Wu
    Pages 1-33
  3. Shan-Ben Chen, Jing Wu
    Pages 35-55
  4. Shan-Ben Chen, Jing Wu
    Pages 57-111
  5. Shan-Ben Chen, Jing Wu
    Pages 113-162
  6. Shan-Ben Chen, Jing Wu
    Pages 163-220
  7. Shan-Ben Chen, Jing Wu
    Pages 275-276
  8. Back Matter
    Pages 277-278

About this book


Welding handicraft is one of the most primordial and traditional technics, mainly by manpower and human experiences. Weld quality and efficiency are, therefore, straitly limited by the welder’s skill. In the modern manufacturing, automatic and robotic welding is becoming an inevitable trend. However, it is difficult for automatic and robotic welding to reach high quality due to the complexity, uncertainty and disturbance during welding process, especially for arc welding dynamics. The information acquirement and real-time control of arc weld pool dynamical process during automatic or robotic welding always are perplexing problems to both technologists in weld field and scientists in automation.

This book presents some application researches on intelligentized methodology in arc welding process, such as machine vision, image processing, fuzzy logical, neural networks, rough set, intelligent control and other artificial intelligence methods for sensing, modeling and intelligent control of arc welding dynamical process.

The studies in the book indicate that the designed vision sensing and control systems are able to partially emulate a skilled welder’s intelligent behaviors: observing, estimating, decision-making and operating, and show a great potential and promising prospect of artificial intelligent technologies in the welding manufacturing.


Arc Welding Dynamical Process Intelligent Control Knowledge Modelling Visual Information Acquiring artificial intelligence intelligence robot sensing

Authors and affiliations

  1. 1.Institute of Welding EngineeringShanghai Jiao Tong UniversityShangahi 200240P R China

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