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Adaptive location of repaired blade for multi-axis milling

  • Wu, Baohai (Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University) ;
  • Wang, Jian (Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University) ;
  • Zhang, Ying (Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University) ;
  • Luo, Ming (Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University)
  • Received : 2015.03.19
  • Accepted : 2015.06.14
  • Published : 2015.10.01

Abstract

Free-form blades are widely used in different industries, such as aero-engine and steam turbine. Blades that are damaged during service or have production deficiencies are usually replaced with new ones. This leads to the waste of expensive material and is not sustainable. However, material and costs can be saved by repairing of locally damaged blades or blades with localized production deficiencies. The blade needs to be further machined after welding process to reach the aerodynamic performance requirements. This paper outlines an adaptive location approach of repaired blade for model reconstruction and NC machining. Firstly, a mathematical model is established to describe the localization problem under constraints. Secondly, by solving the mathematical model, localization of repaired blade for NC machining can be obtained. Furthermore, a more flexible method based on the proposed mathematical model and the continuity of the deformation process is developed to realize a better localization. Thirdly, by rebuilding the model of the repaired blade and extracting repair error, optimized tool paths for NC machining is generated adaptively for each individual part. Finally, three examples are given to validate the proposed method.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China, Aeronautical Science Foundation of China, Central Universities

Cited by

  1. Constructing Process Models of Engine Blade Surfaces for Their Adaptive Machining: An Optimal Approach vol.141, pp.1, 2015, https://doi.org/10.1115/1.4041625
  2. Airfoil profile reconstruction from unorganized noisy point cloud data vol.8, pp.2, 2015, https://doi.org/10.1093/jcde/qwab011