Print Email Facebook Twitter Online non-destructive evaluation in automated fibre placement Title Online non-destructive evaluation in automated fibre placement Author Tonnaer, R. Contributor Shroff, S.C. (mentor) Faculty Aerospace Engineering Department Aerospace Structures and Materials Programme Structural Integrity and Composites Date 2016-11-03 Abstract The strict quality requirements for aerospace composite structures give rise to costly quality control procedures. In automated fibre placement (AFP) these procedures rely heavily on manualwork and inspection. This research aims at performing preventative non-destructive evaluation of composite laminate quality based on an online geometric analysis of the placed fibre. A robot mounted laser pro le sensor, in combination with robot positional data, is used to create a 3D model of the fibre. These are fused using quaternion coordinate transfer operations with the Robot Operating System, an open source robotics platform. The 3D model is converted into an image for fast processing using open source algorithms from OpenCV. Deviations in part-product quality are identified in real-time including geometric, positioning and buckling defects due to high-radius curvatures in the fibre path. Currently the prototype system will give a non-conformance warning to the operator, and in future work it is planned to develop automated feedback and control algorithms to correct common de fects. The implementation of a preventitive system in an industrial fibre placement process can cut back the time spent on inspection and rework. Subject automated fibre placementnon destructive evaluationnon destructive testingRobot Operating Systemqualtiy controlin processonlinepreventativelaminate qualitycomposites To reference this document use: http://resolver.tudelft.nl/uuid:d4c70a99-0c87-4862-a542-24dfc778e684 Part of collection Student theses Document type master thesis Rights (c) 2016 Tonnaer, R. Files PDF RTonnaer - Online non-des ... -Large.pdf 75.44 MB Close viewer /islandora/object/uuid:d4c70a99-0c87-4862-a542-24dfc778e684/datastream/OBJ/view