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Pipe Spatter Detection and Grinding Robot

Sung-Ho Hong, Jaeyoul Lee, Dong-Ho Shin, Jehun Hahm, Jonghwan Baek, Jin-Ho Suh

发表年份
2022
引用次数
3
访问权限
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摘要

This paper proposes a robotic system that automatically identifies and removes spatters generated while removing the back-bead left after the electric resistance welding of the outer and inner surfaces during pipe production. Traditionally, to remove internal spatters on the front and rear of small pipes with diameters of 18–25 cm and lengths of up to 12 m, first, the spatter locations (direction and length) are determined using a camera that is inserted into the pipe, and then a manual grinder is introduced up to the point where spatters were detected. To optimize this process, the proposed robotic system automatically detects spatters by analyzing the images from a front camera and removes them, using a grinder module, based on the spatter location and the circumferential coordinates provided by the detection step. The proposed robot can save work time by reducing the required manual work from two points (the front and back of the pipe) to a single point. Image recognition enables the detection of spatters with sizes between 0.1 and 10 cm with 94% accuracy. The internal average roughness, Ra, of the pipe was confirmed to be 1 µm or less after the spatters were finally removed.

关键词

Artificial intelligenceComputer visionPoint (geometry)RobotEngineeringProcess (computing)GrindingComputer scienceMechanical engineeringMathematics

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