Optimization of a wearable speed monitoring device for welding applications

Abstract

The heat input is a parameter used to ensure quality of submerged metal arc welding, one of the most common metal joining procedures in the manufacturing industry. This parameter is dependent on the current and voltage, defined by the specific welding procedure, along with the welding speed, a feature that is strongly dependent on the hand movement of the welding operator. A wearable speed monitoring device (SMD) was developed by fusing optical and inertial sensor data to measure the handheld device speed of the welder. This work aims at tuning the parameters affecting the performance of SMD prototype by testing it with four batches of common electrodes in a real industrial environment. The outcomes were compared with the results from the traditional manual calculation, namely, a true coarse average (TCA) velocity. At first, observations were performed to identify any scope of improvement for the SMD. Secondly, an optimization of the main parameters was performed by minimizing a cost function involving the TCA velocities for each batch. A final assessment was then performed with the optimized parameters evaluating the achieved results; a comparative analysis showed a reduction of the relative average errors of 32%, 1.4%, and 4.2% for 2.5, 4, and 5 mm electrode sets, respectively. The system was found already optimized for the 3.25-mm electrodes, using baseline parameters with an error of about 12%. The methodology employed in this study can be further utilized in scenarios in which speed monitoring is employed for light-driven applications with a moving reference.