Print Email Facebook Twitter Simulation and detection of flaws in pre-cured CFRP using laser displacement sensing Title Simulation and detection of flaws in pre-cured CFRP using laser displacement sensing Author Miesen, N. Sinke, J. Groves, R.M. Benedictus, R. Faculty Aerospace Engineering Department Aerospace Structures & Materials Date 2015-06-11 Abstract The novelty of the research is the detection of different types of flaws in the prepreg carbon fibre-reinforced fibres (CFRP) layup compared to in cured products. This paper presents the development of a new method for in situ detection of prepreg CFRP production flaws combining laser displacement sensors and analytical modelling. Experimental results are used to validate the results from the models. The pre-cured flaws are simulated to determine the needed specifications of the measurement system. In static and dynamic experiments, the typical production flaws are detected to demonstrate the use of laser displacement sensing as a preventative non-destructive evaluation (NDE) system. During the production of CFRP materials, flaws can be introduced due to the process of layup or curing. Once a production flaw is embedded and cured in the CFRP laminate, the damage is irreversible and it is expensive to rework or remanufacture the product. Laser displacement sensing is currently used in a wide range of applications in industrial manufacturing and is successfully assessed in this research as a preventative NDE system. Subject laser displacement sensingpreventative NDECFRPlayup process To reference this document use: http://resolver.tudelft.nl/uuid:9cf82c49-3e69-45d2-aee8-78727f8064cc Publisher Springer ISSN 0268-3768 Source https://doi.org/10.1007/s00170-015-7305-x Source The International Journal of Advanced Manufacturing Technology, 2015 Part of collection Institutional Repository Document type journal article Rights (c) 2015 The Author(s)This article is published with open access at Springerlink.com Files PDF Miesen_2015.pdf 1.23 MB Close viewer /islandora/object/uuid:9cf82c49-3e69-45d2-aee8-78727f8064cc/datastream/OBJ/view