Rough set based knowledge acquiring method in intelligent detecting system for lack of weld

Knowledge acquisition has been a major concern in intelligent systems, which determines the efficiency of intelligent systems. In 1982, Pawlak put forward rough set theory which is a mathematical tool to deal with vagueness and uncertainty and can be used to find hidden relations in data. So the rough set method has been applied widely when acquiring knowledge. We introduce a rough set based knowledge acquisition method in an intelligent detecting system for lack of weld. This method can acquire welding process knowledge, that is operation characteristics, from workers´ welding data and the running results of the system show the effect of knowledge acquisition can satisfy the need of production.