Real-time seam tracking during narrow gap GMAW process based on the wide dynamic vision sensing method

Abstract

Welding torch horizontal seam tracking is a crucial condition to realize automatic welding of narrow gap gas metal arc welding (NG-GMAW) robots. In the present study, a real-time welding seam tracking technology based on the passive vision sensor is proposed. To this end, a wide dynamic range (WDR) vision sensor is used to capture real-time welding images. In order to realize real-time identification of the welding torch center deviation in the process of swinging arc in a welding bead, a welding seam tracking algorithm based on the window information fusion (WIF) is proposed. In this regard, the local feature moving window recognition (LMWR) algorithm is applied to extract the groove center. Based on the improved welding image processing program, the weld pool center and welding wire center are prepared for seam tracking. In this regard, considering the trifling variation of groove and weld pool center, the welding horizontal deviation is obtained by combining them with welding wire center calculation. Aiming at establishing a correlation between consecutive images, the Kalman filter is used to estimate the deviation optimally. The tracking algorithm is successfully verified in the weld bead with a horizontal deviation, and the tracking accuracy of ±0.47 mm is achieved. The performed analyses demonstrate that the developed algorithm meets the requirements of real-time seam tracking in the GMAW process of the welding robot.