随着焊接传感技术以及信号处理技术的快速发展,人们越来越注重对焊接过程质量控制的研究,而多传感器信息融合技术是焊接质量控制的一种重要的方法,采用该技术实现熔化极气体保护焊(MIG)脉冲焊接质量的自动控制.该技术采用了视觉传感器和电弧传感器将采集的不同的描述信息进行了有效的特征提取和传输,并运用多传感器信息融合算法进行焊缝的跟踪.视觉传感器利用工业电荷耦合元件(CCD)获取图像信息控制焊炬的横向偏差信息,电弧传感器利用数据采集卡获取电流信息控制焊炬的高度互补偏差信息和横向的冗余信息,将两种传感器得到的冗余信息和互补信息在特征层下进行融合实现焊接过程横向和高度的纠偏控制.冗余信息的融合可以实现视觉传感的图像去噪,而互补信息的融合可以进一步提高焊缝跟踪的精度.实验结果表明,所提算法能够较好地提高焊接的质量,从而也验证了算法的有效性和合理性.%With the rapid development of weld sensor technology and signal processing technology, more and more researchers begin to pay attention to the research of the welding process quality control. The multi-sensor information fusion technology is an important method for welding quality control. The technology is applied to the automatic control process of MIC pulse welding quality. This paper captured different description information for the effective feature extraction and transmission with the vision sensor and the arc sensor, which used in multi-sensor information fusion algorithm for seam tracking. The vision sensor obtained image information by industrial Charg-Coupled Device (CCD) for the lateral deviation information of the weld torch, the arc sensor obtained current information by data acquisition card for the height complementary deviation information and lateral redundancy information of the weld torch. The complementary and redundant information of two sensors were used to sensor information fusion on feature level for lateral and height deviation control. The redundant information fusion achieved visual image de-noising, while the complementary information fusion can further improve the seam tracking precision. The experimental results show that the proposed algorithm can improve the welding quality, and thus verify its efficiency and rationality.
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