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：电池技术对全球电气化进程日益重要。然而，电池对制造过程中的微小变化高度敏感，这些变化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，历史上CT扫描在高通量制造中的应用受限于其低吞吐量以及大文件体积的处理难度。本研究呈现了一个包含超千张商用电池生产态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）及多种电池形态（圆柱、软包和方形）。我们共评估了七种不同类型的电池。通过该数据集可观测到制造过程中的变异性和电池缺陷的存在。该数据集对从事电池技术、计算机视觉或跨领域研究的科学家与工程师具有参考价值。