Using photodiodes and statistical evaluation methods for process monitoring tasks during the laser beam welding of stainless-steel foils

Abstract

Besides battery-based mobility solutions, polymer electrolyte membrane fuel cells (PEMFCs) can be utilized to electrify powertrains. Metallic bipolar plates, usually consisting of two thin micro-formed metal foils, are a crucial component of PEMFCs. For the joining of the foils, laser beam welding is the state-of-the-art manufacturing process. Within the scope of this work, a stable parameter window for the welding of AISI 316L was identified. Therefore, an adjustable ring-mode laser beam source in combination with a photodiode-based sensor system for process monitoring was applied. During the experiments, artificial process faults (e.g., contamination of the samples) were introduced to understand their impact on the welding process and the photodiode signals. The welded samples were evaluated using metallographic cross-sections and surface topography scans. Finally, a statistical signal analysis was employed to interpret the data obtained from the photodiodes to distinguish between fault-free and defective weld seams based on specific signal features.