Optimization of a wearable speed monitoring device for welding applications
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ORIGINAL ARTICLE
Optimization of a wearable speed monitoring device for welding applications Abanti S. Afroz 1 & Francesca Digiacomo 1 & Riccardo Pelliccia 1 & Francesco Inglese 1 & Cesare Stefanini 1,2 & Mario Milazzo 1 Received: 17 January 2020 / Accepted: 17 August 2020 / Published online: 22 August 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
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. Keywords Sensor fusion . Welding . Moving reference . Wearable device . Parameter optimization
1 Introduction * Mario Milazzo [email protected] Abanti S. Afroz [email protected] Francesca Digiacomo [email protected] Riccardo Pelliccia [email protected] Francesco Inglese [email protected] Cesare Stefanini [email protected] 1
The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant’ Anna, Viale R. Piaggio 34, 56025 Pontedera, Italy
2
Healthcare Engineering Innovation Center, Khalifa University, Abu Dhabi, UAE
Within the last few decades, human-centered and collaborative technologies have been considered strategic for improving quality in industrial working processes where manual work has been strongly employed [1–5]. Arc welding represents a specific scenario where these approaches can play a key role since this manual process has not been considerably improved for many decades. This activity concerns the procedures, commonly used in the manufacturing indus
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