文章基本信息

标题：Research on Defect Recognition of Lithium Battery Pole Piece Based on Deep Learning
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作者：Jiwei Li ; Linsheng Li ; Changlu Xu 等
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2021
卷号：261
页码：1-5
DOI：10.1051/e3sconf/202126101021
语种：English
出版社：EDP Sciences
摘要：In the field of defect recognition, deep learning technology has the advantages of strong generalization and high accuracy compared with mainstream machine learning technology. This paper proposes a deep learning network model, which first processes the self-made 3, 600 data sets, and then sends them to the built convolutional neural network model for training. The final result can effectively identify the three defects of lithium battery pole pieces. The accuracy rate is 92%. Compared with the structure of the AlexNet model, the model proposed in this paper has higher accuracy.