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Geometric error suppression of six-axis machine tool for blisk full-shape surface grinding via constrained error sensitivity analysis.
- Source :
-
Precision Engineering . Jun2024, Vol. 88, p1-14. 14p. - Publication Year :
- 2024
-
Abstract
- A six-axis machining configuration is proposed to improve the surface quality and finishing efficiency of an aeroengine blisk. It flexibly enlarges the accessible interference-free space of the tool for finishing the full-shape surface, including the blade body, root, and hub surfaces. An error model for tool contact posture with respect to the kinematic axis errors is established, revealing the relationship between the kinematic deviation of the axes and resultant profile error. An improved Sobol method is applied for error sensitivity analysis to identify crucial error terms based on the quasi-Monte Carlo algorithm. In particular, an efficient error sensitivity index is proposed by combining a unified objective function to identify crucial error terms, followed by the simulations and cutting experiments for validation. As a result, the blade profile error was successfully suppressed by approximately 40 % in most. This work provides a fundamental framework for elevating the multi-axis machining accuracy of aeroengine blisk. • A six-axis machine tool has been proposed to achieve the full-shape-surface grinding on the blisk. • A constrained error sensitivity index model was proposed to compensate for key error terms. • Sensitivity analysis was conducted using an improved Sobol method incorporated quasi-Monte-Carlo algorithm. • The effectiveness of error sensitivity analysis and corresponding tool-path-based compensation were verified. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MACHINE tools
*SENSITIVITY analysis
*SURFACE finishing
*QUASI-Newton methods
Subjects
Details
- Language :
- English
- ISSN :
- 01416359
- Volume :
- 88
- Database :
- Academic Search Index
- Journal :
- Precision Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 177906511
- Full Text :
- https://doi.org/10.1016/j.precisioneng.2024.01.021