Influence of ultrasound on pore and crack formation in laser beam welding of nickel-base alloy round bars

Welding by laser beam is a method for creating deep and narrow welds with low influence on the surrounding material. Nevertheless, the microstructure and mechanical properties change, and highly alloyed materials are prone to segregation. A new promising approach for minimizing segregation and its effects like hot cracks is introducing ultrasonic excitation into the specimen. The following investigations are about the effects of different ultrasonic amplitudes (2/4/6 µm) and different positions of the weld pool in the resonant vibration distribution (antinode, centered, and node position) for bead on plate welds on 2.4856 nickel alloy round bars (30 mm diameter) with a laser beam power of 6 kW. The weld is evaluated by visual inspection and metallographic cross sections. The experiments reveal specific mechanisms of interaction between melt and different positions regarding to the vibration shape, which influence weld shape, microstructure, segregation, cracks and pores. Welding with ultrasonic excitation in antinode position improves the welding results

Deep Learning-Based Weld Contour and Defect Detection from Micrographs of Laser Beam Welded Semi-Finished Products

Laser beam welding is used in many areas of industry and research. There are many strategies and approaches to further improve the weld seam properties in laser beam welding. Metallography is often needed to evaluate welded seams. Typically, the images are examined and evaluated by experts. The evaluation process qualitatively provides the properties of the welds. Particularly in times when artificial intelligence is being used more and more in processes, the quantization of properties that could previously only be determined qualitatively is gaining importance. In this contribution, we propose to use deep learning to perform semantic segmentation of micrographs of complex weld areas to achieve the automatic detection and quantization of weld seam properties. A semantic segmentation dataset is created containing 282 labeled images. The training process is performed with DeepLabv3+. The trained model achieves a value of around 95% for weld contour detection and 76.88% of mean intersection over union (mIoU). © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Influence of an oxygen-free atmosphere on laser beam brazing of aluminium with prior surface deoxidation by pulsed laser radiation

Aluminium alloys, like AlMgSi1 and AlMg3, cannot be joined in industrial processes by laser beam brazing without the use of fluxes due to their resistant oxide layer. The aim of this study is to dispense with the use of flux. For the investigations, an oxygen-free atmosphere was created by using the highly reactive gas monosilane and thus achieving O2 partial pressures of 10-18 mbar. After removal of the oxides by a laser source with 1064 nm wavelength, pulse energies of max. 0.3 µJ and pulse durations of 45 ns, reoxidation is prevented by the oxygen-free atmosphere, so that brazing is carried out on an oxide-free material surface. The bead on plate seams show a materially bonded brazed joint in cross-section. Reference experiments without monosilane either show no wetting or an increased melting of base material. The influence of laser beam power for brazing, pulse energy for deoxidation and wire feed was investigated