Real-time Machining Vibration Data Driven Milling Process Parameters Adaptive Optimization

doi:10.3901/JME.2020.23.172

Abstract

Abstract: In order to decrease the influence of machining vibration to the finishing quality and efficiency of the thin-walled parts, this paper proposed a real-time machining vibration data driven milling process parameters adaptive optimization method. Firstly, the chatter stability model is constructed according to the regeneration principle. Next, dividing the measured vibration data of one step into several segments to simulate the material remove process. The stiffness and modal parameters of thin-walled parts is calculated by finite element unit force method and optimized STD method to derive the frequency response function of thin-walled parts, which is used to calculate the 3D stability lobe diagram. Then, taking the maximum material removal rate as the goal, the genetic algorithm is used to calculate the optimized process parameters of next process step considering to avoid the milling chatter and resonance. Repeat the above cycle again until the thin-walled parts milling process is completed. Finally, the feasibility and effectiveness of the method are verified by the assembly interface of aircraft cutting experiment. The experiment results proves that the method can not only shorten the assembly interface milling process time by 33%, but also improve the surface roughness from Ra 3.2 to Ra 1.6.

Key words: real-time vibration data, thin-walled parts, process parameters optimization, process step, optimized STD method

CLC Number:

V262

ZHAO Xiong, ZHENG Lianyu, FAN Wei, YU Lu. Real-time Machining Vibration Data Driven Milling Process Parameters Adaptive Optimization[J]. Journal of Mechanical Engineering, 2020, 56(23): 172-184.

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