电池极片表面缺陷识别与质量分级特征库数据集

本数据集聚焦锂电池极片表面质量检测环节，构建了标准化的 AOI 视觉检测缺陷特征库，完整记录了极片表面缺陷的视觉特征、检测参数与人工复判结果，旨在支撑 AI 缺陷识别模型训练、实现缺陷自动分级，为解决人工检测效率低、漏检误检等问题提供数据支撑。

This dataset focuses on the surface quality inspection process of lithium battery electrode sheets. It has established a standardized defect feature database for AOI visual inspection, and comprehensively documents the visual characteristics, detection parameters and manual re-inspection results of surface defects on these electrode sheets. The dataset aims to support the training of AI-based defect recognition models and enable automatic defect grading, providing reliable data support to address the problems of low efficiency, missed detection and false detection in manual inspection.

搜集汇总

背景与挑战

背景概述

该数据集专注于电池极片表面缺陷的识别与质量分级，由东莞市宏为新能源有限公司基于企业数据构建。它提供了一个特征库，用于支持电池制造过程中的质量控制和缺陷检测，目前处于公示阶段，体现了数据在工业场景中的实际应用潜力。