Abstract
Composite lightweight components of carbon fiber reinforced plastics (CFRP) provide great potential for the automotive industry. Yet, due to their complexity, there is a high amount of quality defects in their production processes. Thus, this article deals with an approach for in-process metrology of CFRP components by means of an eddy-current sensor array. First, the development of the sensor design and its in-process integration is introduced. Second, a method for the quantitative evaluation of the measurement data as well as the measurement uncertainty is elaborated. Finally, a machine learning approach for the classification of crucial defects is shown.
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