Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29648
Title: A reverse engineering based approach for the repair of LP compressor fan blade
Authors: Xin, Y
Man, HC 
O'Brien, S
Keywords: Adaptive machining
CAD/CAM
Free-form
Reverse engineering
Issue Date: 2015
Publisher: euspen
Source: Proceedings of the 15th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2015, 2015, p. 383-384 How to cite?
Journal: Proceedings of the 15th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2015 
Abstract: The aim of this research is to develop an adaptive machining strategy to restore worn fan blades. Since each worn fan blade has its unique profile, a reliable restoration model is essential and can increase the effectiveness and accuracy of the machining result. In comparison with other studies of reverse engineering which focus on enhancing the accuracy of the free-form geometry only with the surface scanning data, the approach introduced in this paper gives a different view in which the reversed engineered fan blade should be based on both its surface character and the design principle. The idea that is applied on the surface measuring strategy and data process algorithm is airfoil segment based which is the basic principle of the blade design. So, a reliable CAD model can be generated with the assist of the design principle. Moreover, this approach can further optimize the blade machining result. A computer simulation system was established. The test raw data was collected from a compressor fan blade which is available in aero engines. The simulation result showed that the restored area was in a reasonable shape and the rest of reconstructed geometry was in accordance with the real part with high accuracy.
Description: 15th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2015, 1-5 June 2015
URI: http://hdl.handle.net/10397/29648
ISBN: 9780956679079
Appears in Collections:Conference Paper

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