Dataset for weld seam analysis and discontinuity prediction in laser beam welding scenarios

Laser beam welding can produce narrow, high-quality welds in various industrial joining processes. The thermal expansion and contraction of the metal during the weld results in the displacement of the sheets. That leads to the formation of joint gaps and subsequent to a process interruption. This behavior has only been analyzed to a limited extent and causes manufacturers to rely on heavy clamping systems rather than using more flexible fixtureless approaches. Due to the time-consuming and costly nature of recording and producing erroneous weld seams, such recordings and datasets are rarely available in this area. This often limits the research towards adaptable fixtureless welding setups. Because of this, we present a multi-modal dataset consisting of 100 recorded welds that tracks the metal sheets movement. The developed setup enables the determination of boundary conditions for fixtureless welding. Two types of sensors record the welding process. First, three inductive probes are applied to record the metal sheets` movement and second, a long-wave infrared (LWIR) camera records changes in the thermal radiation field. Two different welding speeds and laser powers were used to produce a variety of welds. The dataset can be used for data-driven algorithms to predict the metal movement, analyze the thermal radiation field, or develop quality control methodologies.