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DETECTION OF SURFACE DEFECTS ON CARBON FIBER ROVINGS USING LINE SENSORS AND IMAGE PROCESSING ALGORITHMS

机译:使用线传感器和图像处理算法检测碳纤维粗纱上的表面缺陷

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Producing components of carbon fiber reinforced plastics (CFRP) is an established business but still the quality inspection remains a challenge and demands individual solutions. Fraunhofer IGCV focuses on optical measurement systems for quality inspection on carbon fibers and binder applications. These systems aim at monitoring surface structure, pattern, contamination, size, homogeneity and more. With the use of line scan cameras the resolution achieved enables the system to detect flaws like single filament fractures. Also, deviations from ideal patterns can be located. Furthermore, binder distribution is another feature concerning the composites production. In an application developed by Fraunhofer IGCV, the software evaluates binder distribution and its homogeneity. Since every monitoring task requires an adopted image processing pipeline, Fraunhofer IGCV implemented a solution reducing the time needed for the development. With the use of an Evolutionary Computing approach a first step towards a self optimizing defect detection pipeline for flaw detection within carbon fiber production is presented.
机译:生产碳纤维增强塑料(CFRP)的组件是一项既定的业务,但仍然质量检验仍然是一个挑战,并要求各个解决方案。 Fraunhofer IGCV侧重于碳纤维和粘合剂应用的光学测量系统。这些系统旨在监测表面结构,图案,污染,尺寸,均匀性等。随着线扫描相机的使用,所实现的分辨率使系统能够检测单丝骨折等缺陷。而且,可以位于理想图案的偏差。此外,粘合剂分布是有关复合材料生产的另一个特征。在由Fraunhofer IGCV开发的应用中,软件评估了粘合剂分布及其同质性。由于每个监控任务都需要采用的图像处理管道,因此Fraunhofer IGCV实现了减少开发所需时间的解决方案。通过使用进化计算方法,提出了一种朝向自我优化缺陷检测管道进行漏洞检测的第一步。

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