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Automated Visual Inspection of Metallic Parts

Jiang Liu, Yaonan Li, Caijin Pan, Heping Chen, Ning Xi

发表年份
2017
引用次数
4

摘要

The copper alloy casting parts are widely used in the manufacturing of the taps, pipes, motor stators, crafts, and so on. It is required to recognize the casting parts which have the surface blisters during the on-line automatic grinding. In this paper, we propose a high-speed automatic visual inspection system to detect the surface blisters in real time. The casting part is mounted on the manipulator that can automatically adjust the posture of the casting part in the visual inspection system. The images of casting parts are captured by a single high speed industrial camera, then the feature analysis is applied to these images to identify the blisters. The contour and intensity are extracted to describe the surface blister features which are used to train the recognition model. In the experiments, copper alloy taps are inspected after grinding. A KUKA robotic arm is used to move a part to different inspection surfaces, and an Ethernet camera is used to capture the images. It takes about 35ms for processing one captured frame. For the whole casting taps, it takes less than 10s to scan the whole surface. The results show that the failure rate is nearly 0% and false alarm rate is under 2% for each surface blister.

关键词

CastingArtificial intelligenceComputer visionBlistersComputer scienceGrindingFeature (linguistics)Visual inspectionAutomated optical inspectionFrame rate

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