A modified welding image feature extraction algorithm for rotating arc narrow gap MAG welding
2015) ,"A modified welding image feature extraction algorithm for rotating arc narrow gap MAG welding", (2015),"Rough set based modeling for welding groove bottom state in narrow gap MAG welding", If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About
... Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Abstract Purpose -The purpose of this paper is to provide a modified welding image feature extraction algorithm for rotating arc narrow gap metal active-gas welding (MAG) welding, which is significant for improving the accuracy and reliability of the welding process. Design/methodology/approach -An infrared charge-coupled device (CCD) camera was utilized to obtain the welding image by passive vision. The left/right arc position was used as a triggering signal to capture the image when the arc is approaching left/right sidewall. Comparing with the conventional method, the authors' sidewall detection method reduces the interference from arc; the median filter removes the welding spatter; and the size of the arc area was verified to reduce the reflection from welding pool. In addition, the frame loss was also considered in the authors' method. Findings -The modified welding image feature extraction method improves the accuracy and reliability of sidewall edge and arc position detection. Practical implications -The algorithm can be applied to welding seam tracking and penetration control in rotating or swing arc narrow gap welding. Originality/value -The modified welding image feature extraction method is robust to typical interference and, thus, can improve the accuracy and reliability of the detection of sidewall edge and arc position.