Surface integrity has a significant impact on the performance and life cycle of the blisk blade. Residual stress, as one of the important characterization parameters of surface integrity, is closely related to the performance of the aeroengine blisk blade. A certain interval of residual compressive stress can significantly inhibit the generation of microcracks. This paper proposes an optimization method of polishing process parameter interval based on sensitivity analysis. This research studied the effect of polishing parameters of the alumina ACW (abrasive cloth wheel) on the surface residual stress of the GH4169 superalloy blisk blade. Firstly, the experiment was designed by four factors and three levels response surface method, the multiple regression of the experimental data based on Minitab software was used to get a prediction model of polished surface residual stress. And an analysis of variance was performed on the model. Subsequently, the model of relative sensitivity was got based on this model. The sensitivity order of polishing surface residual stress to each polishing parameter was obtained. And the judging method of stable interval and instable interval was put forward. Then, a parameter interval optimization method was proposed, and the optimal interval of process parameters was obtained. Finally, a polishing verification experiment was performed. The results show that: for the polishing of GH4169 superalloy blades, the surface residual stress is most sensitive to the feed rate vf of the ACW, followed by the granularity p and the rotation rate ω, and the compression depth ap is the least sensitive. The optimal interval of polishing process parameters is: the rotation rate ω is [11000 r/min, 11500 r/min], the feed rate vf is [100 mm/min, 200 mm/min], the compression depth ap is [0.6 mm, 1.0 mm], and the granularity p is [400 #, 600 #]. The optimized polishing process parameters can obtain a large and stable surface residual compressive stress, which is helpful to increase fatigue strength of the blisk blade.
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The research was supported by the National Science Foundation of China (No. 51675439).
Xiaojun Lin is a Professor of Northwestern Polytechnical University, Xi’an, China. His research fields mainly include CAD/CAM and automation, high efficiency NC machining, and adaptive polishing technologies for complex surfaces.
Xiaopeng Xin is currently studying in Northwestern Polytechnical University, Xi’an, China. His research fields mainly include CAD/CAM and automation, high-efficiency NC machining, and adaptive polishing technologies for complex surfaces.
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Lin, X., Xin, X., Yang, R. et al. Sensitivity analysis and parameter interval optimization for residual stress in polishing process of GH4169 blisk blade. J Mech Sci Technol 35, 515–524 (2021). https://doi.org/10.1007/s12206-021-0110-6
- Residual stress
- GH4169 blisk blade
- Sensitivity analysis
- Process parameters
- Optimal interval