Weld bead penetration state recognition in GMAW process based on a central auditory perception model

Abstract

Arc sound signals contain abundant information about the welding process, so they are widely adopted to monitor the penetration states of weld bead online. However, the arc sounds are vulnerable to back ground noises, which limits the practical application of them in industry. In this study, a central auditory perception model was proposed. This model through simulating human auditory system to identify the penetration states of weld bead in GMAW process. Firstly, the auditory spectrums of the arc sounds are obtained through auditory peripheral model. Then the shape of auditory spectrums is analyzed by an auditory cortex model. Finally, according to the auditory cortical response, character vectors are built and used to identify the penetration states. The results show that the proposed method has a high accuracy rate in the identification of penetration states of weld bead. This research provides a new method for the online monitoring of welding quality.