Papers by Author: Fang Li

Abstract: To meet the need of the automation and intelligence of welding process, it’s very important to extract the edge of weld seam accurately for seam tracking. According to the characteristics of GMAW (gas metal arc welding), an image sensing system of weld pool region based on CCD (Charge-coupled Device) is established. An improved method of weld seam extraction is presented. Firstly, weld pool region localization method using saliency detection is proposed, and weld seam region is obtained from the right edge of weld pool, then Sobel transformation and computation model is used to extract the edge of weld seam. Experimental results show that our method can obtain a more accurate weld seam edge and cost less than other method.

Abstract: He sensing of the weld pool and controlling of torch at the center of the groove are important problems in back welding of GMAW (Gas Metal Arc Welding) for pipeline, furthermore, the gap of the groove perhaps is varied, which needs an intelligent control strategy to obtain the high welding quality. Fuzzy neural network control method based on BP algorithm is proposed in this paper, from the module of image processing, the corresponding gap location and width can be obtained. Then determine corresponding swing width and speed when weld gap is varied by the network fuzzy inference and calculating Euclidean distance for GMAW variable gap backing welding process. Experiment results show that the designed control method can improve the welding quality compared with traditional fixed swing and the traditional auto swing.