Multi-Modal Recognition Control System for Real-Time Robot Welding Penetration Control and Quality Enhancement

Abstract

Robot welding penetration control is an important research topic in the field of robot welding online control. This study proposes a recognition control system for multi-modal signals with multiple welding parameters for robot welding penetration control. In this study, a filter bank suitable for welding environments was proposed for welding acoustic signals, and separation and contour extraction algorithms were designed for the welding image signals. Taking the acoustic and image signals as inputs, a multi-modal hybrid model and multiparameter controller were established that can effectively classify and identify the welding penetration state. The penetration state was used as a reference input to the controller for controlling the welding speed and current in real-time. In addition, a digital twin system was developed in this study and deployed on the main and edge computers. The test results show that the system and model can accurately identify the weld penetration, regulate the welding speed and welding current, control the width of the backside molten pool, and improve the welding quality.