Abstract
The objective of the paper is to develop a monitoring structure of an electrical welding process based on noise arc signals analysis, signals generated by the process himself. Because the most important Metal Inert Gas (MIG) welding process is the spray regime, this regime was divided into three sub-regimes named: slow, medium and fast. The monitoring structure is based on signals analysis and spectra classification. The fuzzy supervision structure is based on noise signals spectra and can be used also for control purposes. The information obtained from monitoring can be further useful for the diagnosis of the welding process and to adjust or control the welding operating regimes.
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