Battery technology is increasingly important for global electrification efforts. However, batteries are highly sensitive to small manufacturing variations that can induce reliability or safety issues. An important technology for battery quality control is computed tomography (CT) scanning, which is widely used for non-destructive 3D inspection across a variety of clinical and industrial applications. Historically, however, the utility of CT scanning for high-volume manufacturing has been limited by its low throughput as well as the difficulty of handling its large file sizes. In this work, we present a dataset of over one thousand CT scans of as-produced commercially available batteries. The dataset spans various chemistries (lithium-ion and sodium-ion) as well as various battery form factors (cylindrical, pouch, and prismatic). We evaluate seven different battery types in total. The manufacturing variability and the presence of battery defects can be observed via this dataset. This dataset may be of interest to scientists and engineers working on battery technology, computer vision, or both.

翻译：电池技术在全球电气化进程中日益重要。然而，电池对制造过程中的微小变化极为敏感，这些变化可能引发可靠性或安全问题。计算机断层扫描（CT）是电池质量控制的关键技术，广泛应用于临床和工业领域的非破坏性三维检测。然而，长期以来，低通量及大文件处理困难限制了CT扫描在规模化生产中的实用性。本研究提出一个包含千余枚市售成品电池CT扫描的数据集，涵盖锂离子与钠离子等多种电化学体系，以及圆柱、软包、方形等不同电池形态。数据集共评估七类电池，可观察制造变异与电池缺陷。该数据集对从事电池技术、计算机视觉或交叉领域研究的科研人员与工程师具有参考价值。