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：电池技术对于全球电气化进程日益重要。然而，电池对微小的制造差异高度敏感，这些差异可能引发可靠性或安全性问题。计算机断层扫描（CT）是电池质量控制的重要技术，广泛应用于临床和工业领域的非破坏性三维检测。然而，CT扫描在高产量制造中的应用长期受限于其低吞吐量以及大文件尺寸的处理难题。本研究提出了一个包含一千余张商用成品电池CT扫描图像的数据集。该数据集涵盖多种化学体系（锂离子和钠离子）及不同电池形态（圆柱形、软包和方形），共评估七种不同类型电池。通过该数据集可观测到制造差异和电池缺陷的存在。本数据集可为从事电池技术、计算机视觉或跨学科研究的科研人员和工程师提供重要参考。