Welding handicraft is one of the most primordial and traditional
technics, mainly by manpower and human experiences. Weld quality and
ef?ciency 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 dif?cult for au- matic 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 te- nologist in weld ?eld 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 arti?cial intelligence me- ods for
sensing, modeling and intelligent control of arc welding dynamical
process. The studies in the book indicate that the designed vision
sensing and control s- tems are able to partially emulate a skilled
welder's intelligent behaviors: observing, estimating, decision-making
and operating, and show a great potential and prom- ing prospect of
arti?cial intelligent technologies in the welding manufacturing.