Abstract
The arc welding process is so complex that the classical modeling method cannot obtain the model effectively. However, the model of the arc welding process is necessary for the intelligent control of the process. Therefore, the modeling has been the interest of many researchers. Recently, more and more researchers are attempting to obtain the model of the process by means of intelligent methods, such as the neural network method, the fuzzy set method, and so on. All these methods concentrate on simulating the intelligent behavior of human beings, namely using human experience. Many applications of these methods have proved their effectiveness under certain conditions. However, their limits are obvious and further research is needed. This paper proposes a method of rough set based knowledge modeling for the aluminum alloy pulsed gas tungsten arc welding (GTAW) process. Owing to the ability of dealing with knowledge (experience) of the rough set theory, the method can obtain the knowledge model of the aluminum alloy pulsed GTAW process. The model obtained is easily understood and revised. Experiment results indicate that the method is effective. The method can be regarded as the basis of the intelligent control of the welding process .
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The International Journal of Advanced Manufacturing Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
