Abstract

In order to reduce the cost of lithium-ion batteries, production scrap has to be minimized. The reliable detection of electrode defects allows for a quality control and fast operator reaction in ideal closed control loops and a well-founded decision regarding whether a piece of electrode is scrap. A widely used inline system for defect detection is an optical detection system based on line scan cameras and specialized lighting. The cameras scan the electrode, and brightness differences on the surface are detected and processed inline. The characteristics of the defect image are used for automated classification of the defects based on image features. Furthermore, the detailed detection of defects allows for the identification of causes. This paper describes the working principle of such an inline detection system, the catalog of typical defects, and the image features used to classify them automatically. Furthermore, we propose and discuss causes and effects of the different defect types on the basis of the literature and expert experience. In combination with tracking and tracing, this enables the manufacturer to reduce scrap by detecting defects early in the production chain.

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