Gray correlation study of milling surface roughness and milling vibration of titanium alloy

Titanium alloy, characterized by high strength and excellent corrosion resistance, has extensive applications in the manufacturing of precision components across numerous high-end sectors. Therefore, it is important to optimize the milling process for titanium alloys. A series of tests on titanium alloys were conducted under different milling parameters, a self-constructed vibration measurement system was used to collect the vibration signals generated in the milling process, and a surface roughness measurement system was used to obtain the workpiece surface roughness. Based on the collected data, the gray-correlation algorithm was used to analyze the correlation degree between the surface roughness and its influence factors. As a result, the gray-correlation value between the surface roughness and the milling vibration was successfully obtained, and the most significant influence factor was determined. Then, with the least-squares method as the theoretical foundation, a program was written using Matlab software to construct a prediction model of surface roughness.