Work

Error prediction for machining thin-walled blade with Kriging model

Year: 2025

Type: article

Abstract: • Prediction models for the position error and torsion error of blades are developed. • The relationship between cutting parameters and error is captured using Kriging model. • The effect of machining parameters on position and torsion errors is analyzed. • Higher or lower spindle speeds increase the position and torsion errors of blades. Compressor blades are the key components of aero-engines, and their machining accuracy is critical to aero-engine performance. However, the choice of machining parameters during machining compressor blade has a direct impact on the position error and torsion error, which in turn affects the aero-engine performance. The conventional methodology for investigating mechanisms on machining error is frequently both time-consuming and labour-intensive. The agent-based modelling approach is trained on a limited set of experimental data in order to obtain an approximate mathematical model of the real process. This approach has the advantages of low modelling cost, convenient operation, and high computational efficiency. Accordingly, this paper employs the agent model to construct prediction models for the position error and torsion error of compressor blades. Firstly, experiments were designed to be conducted on compressor blades under different working conditions in order to obtain the position error and torsion error data of compressor blades. Then, based on the superiority of the agent model, the Kriging models are constructed to establish prediction models for the position error and torsion error of compressor blades. Finally, the influence of machining parameters on the position error and torsion error of compressor blades is analysed. The prediction accuracies of the established models are all greater than 0.85, which can provide strong support for the optimization of the machining process of compressor blades.

Source: Results in Engineering

DOI: 10.1016/j.rineng.2025.104645

Authors: Jinhua Zhou, Sitong Qian, Tong Han, Rui Zhang, Junxue Ren

Institutions: Northwestern Polytechnical University, China Aerospace Science and Technology Corporation

Language: English

Topic: Advanced machining processes and optimization

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,940

Funders: National Natural Science Foundation of China, National Major Science and Technology Projects of China, Natural Science Basic Research Program of Shaanxi Province