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Electronics

Battery Tab Defect Check

Check both battery tabs and their connections for defects

Battery Tab Defect Check

Zugehörige Produkte

In-Sight D900

In-Sight D900

Ausgestattet mit der In-Sight ViDi Deep-Learning-basierten Vision-Software

ViDi software with all defect detection tools

VisionPro Deep Learning

Ein völlig neuer Ansatz bei komplexen Prüfungen, Teilelokalisierung, Klassifikation und OCR

Pouch battery electrodes connect to external circuits with metal tabs. These metallic foil tabs are made from a variety of metals, are thin and soft, and can be easily damaged. Typical defects include scratches, bumps, holes, and dust. Damaged tabs reduce or prevent connectivity, which is why they must be free from defects before being soldered to the electrodes.

However, improper soldering also leads to defects such as burns, hits, and missing balls. Poor solders lead to reduced or missing connectivity and performance reduction.

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To identify both tab and tab solder defects, Cognex Deep Learning’s defect detection tool is trained on a wide selection of undamaged tabs and properly soldered tabs to learn the full variation of normal parts, including the acceptable level of cosmetic defects.

As it scans through the battery tab connections it analyzes and flags any tabs or tab solders that are outside of the acceptable range, while minimizing false positives from purely cosmetic defects. It makes these distinctions despite variations in contrast and background.

Cognex Deep Learning’s classification tool can then train on a range of labelled tab and tab solder defects and learn to categorize specific defect types, such as scratches, holes, and bumps on the tab or burn, hit, or missing ball on the solder. These categorized defects can then be used for upstream process control to minimize defects over time.

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