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In the processes of automatic welding of container girders, the uneven strong reflection on the workpiece surfaces, arc light, splash, and smoke easily led to inaccurate or difficult identification of weld deviations, so a welding seam tracking system for gas metal arc welding of container girders was proposed. Based on a low-cost structured light vision sensor, a highly robust welding seam feature extraction model was established. The linear slope of the laser stripes was used by the model for optimizing the random sampling processes of the random sampling consistency algorithm which achieved stable extraction of weld feature in complex environments. The welding test results on the surface of uneven and strong reflective workpieces show that the average detection errors of the method in the Y and Z directions are as 0.22 mm respectively and 0.19 mm with the welding parameters of 300 A, 29 V, and 1m/min, which achieves stable high precision welding seam tracking. [ABSTRACT FROM AUTHOR]

Ａｉｍｉｎｇ ａｔ ｔｈｅ ｏｎｌｉｎｅ ｑｕａｌｉｔｙ ｉｎｓｐｅｃｔｉｏｎ ｏｆ ｗｅｌｄｅｄ ｓｉｌｉｃｏｎ ｂａｔｔｅｒｙ ｃｈｉｐｓꎬ ａｎ ｏｎｌｉｎｅ ｑｕａｌｉｔｙ ｉｎｓｐｅｃｔｉｏｎ ｍｅｔｈｏｄ ｏｆ ｗｅｌｄｅｄ ｓｉｌｉｃｏｎ ｂａｔ￣ ｔｅｒｙ ｃｈｉｐｓ ｂａｓｅｄ ｏｎ ｖｉｓｕａｌ ｉｄｅｎｔｉｆｉｃａｔｉｏｎ ｔｅｃｈｎｏｌｏｇｙ ｗａｓ ｐｒｏｐｏｓｅｄ ｉｎ ｔｈｉｓ ｐａｐｅｒꎬ ｉｎｃｌｕｄｉｎｇ ｆｅａｔｕｒｅ ｒｅｃｏｇｎｉｔｉｏｎ ａｎｄ ｖｉｓｕａｌ ｍｅａｓｕｒｅｍｅｎｔ. Ｉｎ ｔｈｅ ｆｅａｔｕｒｅ ｒｅｃｏｇｎｉｔｉｏｎ ｓｔａｇｅꎬ ａｎ ｉｍｐｒｏｖｅｄ ｒｅｇｉｏｎ ｇｒｏｗｉｎｇ ａｌｇｏｒｉｔｈｍ ｗａｓ ｐｒｏｐｏｓｅｄ ｔｏ ｆｉｎｉｓｈ ｔｈｅ ｈｉｇｈ￣ｓｐｅｅｄ ａｎｄ ｓｔａｂｌｅ ｄｅｔｅｃｔｉｏｎ ｏｆ ｇｒｉｄｌｉｎｅ￣ｆｒａｃｔｕｒｅ ｆｅａｔｕｒｅｓꎻ Ｆｏｒ ｔｈｅ ｓｃｒａｔｃｈ ａｎｄ ｄｉｒｔｙ ｆｅａｔｕｒｅｓ ｃａｕｓｅｄ ｂｙ ｗｅｌｄｉｎｇꎬ ｔｈｅ ｒｅｇｉｏｎｓ ｏｆ ｉｎｔｅｒｅｓｔ ｗａｓ ａｄａｐｔｉｖｅ ｔｈｒｅｓｈｏｌｄｅｄꎬ ｔｈｅｎ ｔｈｅ ｄｅｆｅｃｔｓ ｗｅｒｅ ｆｉｌｔｅｒｅｄ ｂｙ ｉｎｖａｒｉａｎｔ ｍｏｍｅｎｔｓ ｆｅａｔｕｒｅ. Ｉｎ ｔｈｅ ｆｉｅｌｄ ｏｆ ｖｉｓｕａｌ ｍｅａｓｕｒｅｍｅｎｔꎬ ｕｓｉｎｇ ｔｈｅ ｓｙｍｍｅｔｒｙ ｏｆ ｔａｒｇｅｔ ｉｍａｇｅꎬ ｐｉｘｅｌ ｂａｓｅｄ ｍｅａｓｕｒｅｍｅｎｔｓ ｏｆ ｓｏｌｄｅｒ ｓｔｒｉｐ ｏｆｆｓｅｔｓ ａｎｄ ｃｈｉｐ ｓｐａｃｉｎｇｓ ｗｅｒｅ ｃａｒｒｉｅｄ ｏｕｔ ｔｈｒｏｕｇｈ ａ ｎｕｍｂｅｒ ｏｆ ｓａｍｐｌｉｎｇ ｒｅｃｔａｎｇｌｅｓ. Ｔｈｅ ａｃｑｕｉｓｉｔｉｏｎ ｏｆ ｉｎｔｅｒ ｃｈｉｐ ｉｍａｇｅｓ ａｔ ｅａｃｈ ｔｒａｎｓ￣ ｍｉｓｓｉｏｎ ｂｅａｔ ｗａｓ ｅｎａｂｌｅｄꎬ ｔｈｅ ｏｒｉｇｉｎａｌ ｉｍａｇｅ ｗａｓ ｓｅｇｍｅｎｔｅｄ ｉｎｔｏ ａ ｎｕｍｂｅｒ ｏｆ ｒｅｇｉｏｎｓ ｏｆ ｉｎｔｅｒｅｓｔ ｂｙ ｔｈｅ ｅｄｇｅ ｌｏｃａｔｉｏｎ ｍｅｔｈｏｄꎬｓｏ ｔｈａｔ ｈｉｇｈ￣ ｓｐｅｅｄ ｏｎｌｉｎｅ ｄｅｔｅｃｔｉｏｎ ｗａｓ ｃｏｍｐｌｅｔｅｄ. Ｔｈｅ ｒｅｓｕｌｔｓ ｏｆ ａｃｔｕａｌ ｏｎｌｉｎｅ ｔｅｓｔ ｉｎｄｉｃａｔｅ ｔｈａｔꎬ ｔｈｅ ｖｉｓｕａｌ ｉｎｓｐｅｃｔｉｏｎ ｍｅｔｈｏｄ ｏｆ ｗｅｌｄｅｄ ｓｉｌｉｃｏｎ ｂａｔｔｅｒｙ ｃｈｉｐｓ ｃａｎ ｉｄｅｎｔｉｆｙ ｔａｒｇｅｔ ｄｅｆｅｃｔｓ ｑｕｉｃｋｌｙ ａｎｄ ａｃｃｕｒａｔｅｌｙꎬ ａｎｄ ｉｔ ｈａｓ ｔｈｅ ｃｈａｒａｃｔｅｒｉｓｔｉｃｓ ｏｆ ｇｏｏｄ ｒｅｃｏｇｎｉｔｉｏｎ ｓｔａｂｉｌｉｔｙ. [ABSTRACT FROM AUTHOR]