AI-driven autonomous adaptative feedback welding machine

Welding in the World, vol. 69, pp. 1419–1426

Abstract

Abstract The gas tungsten arc welding (GTAW) is a primary method for nuclear component fabrication and repair. Recent advancements in monitoring and automation technologies have made the shift toward fully automated arc welding more feasible, reducing the necessity for continuous human oversight. Two artificial intelligence-based networks were developed that utilize sensor-based feedback on a mechanized GTAW head. We present an image-based semantic segmentation convolutional neural network that identifies crucial features such as the weld pool, groove, wire, and electrode based on which geometric measurements are derived. A separate novel neural network predicts the weld bead geometry for multi-pass welds and inconsistent groove geometries. The application of both neural networks is a pre-requisite that enables the autonomous planning and execution of multi-pass welds to fill a groove.

Authors 8

1. Benedikt von Querfurth Aachen Fraunhofer Institute for Laser Technology (ILT)

   Fraunhofer Institute for Laser Technology

   Affiliation as printed

   Fraunhofer Institute for Laser Technology (ILT), 52074, Aachen, Germany

2. Shems-Eddine Belhout

   Electric Power Research Institute

   Affiliation as printed

   Electric Power Research Institute (EPRI), Charlotte, NC, 28262, USA

3. Christian Knaak Aachen Fraunhofer Institute for Laser Technology (ILT)

   Fraunhofer Institute for Laser Technology

   Affiliation as printed

   Fraunhofer Institute for Laser Technology (ILT), 52074, Aachen, Germany

4. Stefan Mann corresponding Aachen Fraunhofer Institute for Laser Technology (ILT)

   Fraunhofer Institute for Laser Technology

   Affiliation as printed

   Fraunhofer Institute for Laser Technology (ILT), 52074, Aachen, Germany

5. Carlo Holly Aachen Fraunhofer Institute for Laser Technology (ILT)

   Fraunhofer Institute for Laser Technology · RWTH Aachen University

   Affiliation as printed

   Fraunhofer Institute for Laser Technology (ILT), 52074, Aachen, Germany

   RWTH Aachen University TOS – Chair for Technology of Optical Systems, 52074, Aachen, Germany

6. Jonathan K. Tatman corresponding

   Electric Power Research Institute

   Affiliation as printed

   Electric Power Research Institute (EPRI), Charlotte, NC, 28262, USA

7. Darren Barborak

   Electric Power Research Institute

   Affiliation as printed

   Electric Power Research Institute (EPRI), Charlotte, NC, 28262, USA

8. Mitch Hargadine

   Electric Power Research Institute

   Affiliation as printed

   Electric Power Research Institute (EPRI), Charlotte, NC, 28262, USA