Research on the Analysis and Prediction Model of Machining Parameters of Titanium Alloy by Abrasive Belt

As a high-performance and difficult-to-machine material for the manufacture of blades, titanium alloys are increasingly being used in high-end manufacturing industries such as aerospace and aircraft. As engineering applications become more demanding, so do the requirements for precision. However, to date, the choice of blade grinding parameters is still mainly dependent on the traditional trial cut and experience method, making the processing efficiency low and the quality of processing difficult to be guaranteed. In order to achieve the requirements of high precision and low surface roughness of the workpiece, to get rid of the status quo of relying on manual decision-making, and to achieve reasonable prediction and control of surface quality, this paper proposes to establish a theoretical prediction model for surface roughness of titanium alloy by abrasive belt grinding, and to analyze the influence of the main process parameters on surface roughness during the grinding process through experiments. A theoretical prediction model for surface roughness was developed. The experimental results show that the model has certain accuracy and reliability, and can provide guidance for the high-precision prediction of the surface roughness of ground titanium alloy blades, which has strong practical significance in engineering.

Automated summary

Titanium alloys, as high-performance and difficult-to-machine materials, are increasingly used in high-end manufacturing industries such as aerospace. However, the choice of blade grinding parameters still relies on traditional trial and error methods, resulting in low processing efficiency and uncertain processing quality. In order to achieve high precision and low surface roughness, this paper proposes a theoretical prediction model for surface roughness during abrasive belt grinding of titanium alloy, and analyzes the influence of main process parameters through experiments. The developed model shows certain accuracy and reliability, providing guidance for high-precision prediction of surface roughness and having practical significance in engineering.