Investigation on the Initial Residual Stress Detection Method and Its Application for Deformation Analysis in Machining Thin-Walled Blades
Article
Figures
Metrics
Preview PDF
Reference
Related
Cited by
Materials
Abstract:
The thin-walled blade is a crucial component of aero engines, which is highly susceptible to significant deformation during the machining process. Existing research on deformation control focuses on reducing cutting force and machining-induced residual stress (MIRS). The initial residual stress (IRS) generated in the process of heat treatment and forging is used to reduce the deformation of thin-walled parts under the influence of cutting force and MIRS. Because the IRS measurement is difficult and destructive, this paper proposes a reverse identification method of IRS to measure the IRS of Ti6Al4V. The proposed method is more consistent with the trend of stress and deformation distribution compared with the conventional method. To investigate and decouple the interplay between IRS, MIRS and cutting force on machining deformation, this study employs a curved blade for experimental validation and develops a finite element model to predict the deformation. It is found that cutting force accounts for 46.17% of the deformation with an average value of 26.36 μm, while MIRS accounts for 53.83% with an average value of 30.70 μm. Coupling IRS reduces MIRS maximum deflection deformation from 35.32 μm to 15.50 μm, which provides a new approach to optimize machining deformation through IRS distribution.
Keywords:
Project Supported:
This work was financially supported in part by the National Key Research and Development Program of China (No.2022YFB3404803) and the National Natural Science Foundation of China (No.92160301).
ZHANG Hua, ZHAO Shengqiang, SUN Hao, PENG Fangyu, YAN Rong, TANG Xiaowei, SHAN Yunan. Investigation on the Initial Residual Stress Detection Method and Its Application for Deformation Analysis in Machining Thin-Walled Blades[J]. Transactions of Nanjing University of Aeronautics & Astronautics,2024,(2):158-173