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In order to recognize various metal transfer modes, by the creation of a pattern recognition system for metal transfer mode, five kinds of spectrum signal in gas metal arc welding (MIG, MAG and CO2) are collected and taken as training samples. These samples are pretreated by computer. Several key characteristic parameters of the spectrum signal are creatively extracted, and a corresponding recognition function and a minimum-distance-classifier are constructed. The results show that using this method, the pattern recognition of several kinds of metal transfer mode for the metal gas arc welding can be done successfully. It has good accuracy and recognition precision, basis for controlling the metal gas arc welding metal transfer automatically, and relative important parameters in welding process, such as the frequency of droplet transfer and the approximate diameter of each droplet, can also be obtained.
The order of recognizing various metal transfer modes, by the creation of a pattern recognition system for metal transfer mode, five kinds of spectrum signal in gas metal arc welding (MIG, MAG and CO2) are collected and taken as training samples. Several key characteristic parameters of the spectrum signal are creatively extracted, and a corresponding recognition function and a minimum-distance-classifier are constructed. The results show that using this method, the pattern recognition of several kinds of metal transfer mode for the metal gas arc welding can be done successfully. It has good accuracy and recognition precision, basis for controlling the metal gas arc welding metal transfer automatically, and relative important parameters in welding process, such as the frequency of droplet transfer and the approximate diameter of each droplet, can also be obtained.