The present development trend in lightweight construction is characterised by an increased application of material-hybrid transition areas which are frequently involved with an intensified and considerably challenging quality concern.

This research explores a complete referencing process in order to acquire statistically secured datasets in the field of non-destructive inspection of CFRP metal hybrid components via optical lock-in thermography by introducing a novel defect abstraction method. Thereby, the knowledge-based management of the generated datasets constitutes the ultimate scope. The experimentally determined datasets comprise both an examiner-specific probability of detection and an adequate defect visibility in a preferably short measurement time.

轻质结构的当前发展趋势的特征是增加了材料-混合过渡区域的应用，这些材料通常涉及强度和相当具有挑战性的质量问题。

这项研究探索了一个完整的参考过程，以通过引入一种新颖的缺陷提取方法，通过光学锁定热成像技术来获取CFRP金属混合组件的非破坏性检查领域的统计安全数据集。因此，所生成数据集的基于知识的管理构成了最终范围。实验确定的数据集包括检查员特定的检测概率和在较短的测量时间内（足够短的时间内）足够的缺陷可见性。