High-Precision Adjustment of Welding Depth during Laser Micro Welding of Copper Using Superpositioned Spatial and Temporal Power Modulation

For joining metallic materials for battery applications such as copper and stainless steel, laser beam micro welding with beam sources in the near-infrared range has become established in recent years. In laser beam micro welding, spatial power modulation describes the superposition of the linear feed motion with an oscillating motion. This modulation method serves to widen the cross-section of the weld seam as well as to increase the process stability. Temporal power modulation refers to the controlled modulation of the laser power over time during the welding process. In this paper, the superposition of both temporal and spatial power modulation methods is presented, which enables a variable control of the weld penetration depth. Three weld geometries transverse to the feed direction are part of this investigation: the compensation of the weld penetration depth due to the asymmetric path movement during spatial power modulation only, a W-shaped weld profile, and a V-shaped. The weld geometries are investigated by the bed on plate weld tests with CuSn6. Furthermore, the use of combined power modulation for welding tests in butt joint configuration between CuSn6 and stainless steel 1.4301 with different material properties is investigated. The study shows the possibility of precise control of the welding depth by this methodology. Depending on the material combination, the desired regions with maximum and minimum welding depth can be achieved by the control of local and temporal power modulation on the material surface.

Sequential Temporal Anticipation Characterized by Neural Power Modulation and in Recurrent Neural Networks

Complex human behaviors involve perceiving continuous stimuli and planning actions at sequential time points, such as in perceiving/producing speech and music. To guide adaptive behavior, the brain needs to internally anticipate a sequence of prospective moments. How does the brain achieve this sequential temporal anticipation without relying on any external timing cues? To answer this question, we designed a premembering task: we tagged three temporal locations in white noise by asking human listeners to detect a tone presented at one of the temporal locations. We selectively probed the anticipating processes guided by memory in trials with only flat noise using novel modulation analyses. A multiscale anticipating scheme was revealed: the neural power modulation in the delta band encodes noise duration on a supra-second scale; the modulations in the alpha-beta band range mark the tagged temporal locations on a subsecond scale and correlate with tone detection performance. To unveil the functional role of those neural observations, we turned to recurrent neural networks (RNNs) optimized for the behavioral task. The RNN hidden dynamics resembled the neural modulations; further analyses and perturbations on RNNs suggest that the neural power modulations in the alpha/beta band emerged as a result of selectively suppressing irrelevant noise periods and increasing sensitivity to the anticipated temporal locations. Our neural, behavioral, and modelling findings convergingly demonstrate that the sequential temporal anticipation involves a process of dynamic gain control: to anticipate a few meaningful moments is also to actively ignore irrelevant events that happen most of the time.