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This product is integrated with a robotic arm, an endoscope module, and a workbench, equipped with key technologies such as deep vision perception and robotic arm motion control. It achieves collaborative linkage between the camera and the robotic arm, and combines industrial AI, deep learning, and big data analysis capabilities to focus on automated visual inspection of precision die-casting inner cavities.
The device relies on deep learning image algorithms to accurately identify burrs, scratches, cracks, stains, slag inclusions, uneven spraying, steps, over milling, thread defects, and various processing anomalies on the inner cavity surface. It supports photography, video recording, and image capture storage, with convenient operation, wide adaptability, and full traceability of detection data. It can quickly achieve lightweight and flexible deployment, greatly improving detection efficiency and defect recognition accuracy in the quality control process of production and manufacturing.
Can simultaneously test 3-5 or more products
Capable of detecting 100-500 stable runs per minute
Can detect multiple product sizes with an accuracy of ± 0.001
The accuracy of batch testing products can reach 99.9%
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