Milling distortion prediction for thin-walled component based on the average MIRS in specimen machining

Zhongxi Zhang, Zhao Zhang, Dinghua Zhang, Ming Luo

科研成果: 期刊稿件文章同行评审

24 引用 (Scopus)

摘要

Machining-induced residual stress (MIRS) has significant effects on the distortion of thin-walled part, especially for the titanium alloy and superalloy parts with complex shape. However, the MIRS is hard to accurately predict through analytical modeling and finite element simulation. In addition, the measurement of MIRS is time-consuming and costly. Therefore, the MIRS caused distortion is hard to accurately predict. In the present study, a novel method is introduced to calculate the average value of MIRS by milling a thin-walled specimen and measuring the distortion, and predict the distortion of the thin-walled component with the calculated average MIRSs. Firstly, the mathematical relationship between the average MIRS and the distortion of specimen is established by analyzing the distribution of residual stress after machining and distortion. In order to estimate the average MIRS accurately, the curvatures of the distorted specimen in both directions are calculated by processing the specimen and measuring the distortion. Based on the calculated average MIRS and the finite element method (FEM), the distortion of the thin-walled component caused by MIRS can be accurately predicted. After that, a relative error calculation model for equivalent bending moment is constructed to assess the algorithm. Subsequently, two-piece of thin-walled specimens are milled to calculate the average MIRSs. Finally, the thin-walled plate and a simplified blade are milled with the same machining parameters to verify the presented method. The result demonstrates the satisfactory agreement between the measured and simulated distortion with the error less than 20%.

源语言英语
页(从-至)3379-3392
页数14
期刊International Journal of Advanced Manufacturing Technology
111
11-12
DOI
出版状态已出版 - 12月 2020

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