Abstract

In this paper, a fuzzy pattern recognition technique is applied to classifying aluminium weld quality in tungsten inert gas (TIG) welding. The pattern vector includes three components, that is, the front height, the back height, and the front width of weld. Based on the values of the pattern vector, good, fair, and poor weld qualities can be automatically classified by using the fuzzy pattern recognition technique. Experimental results under different welding parameters are presented to illustrate the proposed method.

Full Text
Paper version not known

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 call

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.