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Robotics and surface-adaptive ultrasound for fully-automated inspection of composites

机译:机器人和表面适应性超声波,可对复合材料进行全自动检查

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摘要

Surface-Adaptive Ultrasound (SAUL) is a very recent advancement in phased-array technology that is being used to overcome inspec-tion challenges that include highly contoured surfaces, parts with small radii such as those often found on blades and stiffeners, rough and irregular surfaces including regions of ply drop-off and lap joints, and parts with varying shape, curvature, and thickness with length. Although vision systems and robots can be used to achieve highly accurate part following, the part-to-part variability that is typically encountered with composites creates problems for automated part and probe positioning, as well as accurate part tracking. This paper demonstrates the performance of a cost-effective inspection solution for complex-geometry composites in a high-volume production environment achieved by combining advanced ultrasound technology with industrial robotics and vision technologies.
机译:表面自适应超声(SAUL)是相控阵技术的最新进展,用于克服检查挑战,包括高轮廓的表面,半径较小的零件(例如叶片和加劲肋上经常发现的零件,粗糙和不规则的零件)表面,包括帘布层脱落和搭接的区域,以及形状,曲率和厚度随长度变化的零件。尽管可以使用视觉系统和机器人来实现高度精确的零件跟踪,但是复合材料通常会遇到零件间差异的问题,这会给自动零件和探头定位以及精确的零件跟踪带来麻烦。本文演示了通过将先进的超声技术与工业机器人技术和视觉技术相结合,在大批量生产环境中为复杂几何形状的复合材料提供具有成本效益的检测解决方案的性能。

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