Research On Prediction And Controlling Strategies Of Low-rigidity Components Deflections In Peripheral Finish Milling

Low-rigidity components such as integrated wall plate, integrated swing and jet engine impeller account for high proportion in the aerospace industry. Peripheral milling process is widely used in machining low-rigidity components. Due to the low-rigidity of the work piece, deflection errors induced by cutting force cause a common problem that influences significantly the accuracy and the surface quality, even leads to useless products. Consequently, investigations on the prediction and control of the deflection errors during the milling process are of great significance to improve the accuracy and the surface quality, make the process more effective, and establish the adaptive precision NC(Numerical Control) machining. Aiming at the error prediction and control in peripheral finish milling process of low-rigidity components, as following this paper discusses and proposes effective prediction and control methods based on the metal cutting mechanics, finite element method, and NC machining technology.Firstly investigations on the error prediction in peripheral milling process are carried out. Based on the metal cutting mechanics, considering the deflection is mainly induced by cutting force, the finite element prediction model of deflection errors is established after simplifying the cutting process, and the cutting force is modeled as a dynamic moving load acting on the tool work piece contact zone in the milling process. A thin-walled rectangle plate and an impeller blade with complex surface are simulated to predict deflection errors for examples. This work lays a theory foundation for following control strategies and experiment analysis.In succession, this paper demonstrates error compensation strategies to control and eliminate the error after error prediction. Taking thin-walled rectangle plate for example, a strategy combining cutting location offset with tool axis swing is illustrated to compensate both X direction and Z direction errors. This work is the fundamental to be compared with NC experiments.Finally, experiments are implemented to verify the prediction results and compensation strategies. On the one hand, it demonstrates the prediction method is reliable by comparing predicted errors with measured errors before compensation. On the other hand, it also demonstrates the proposed compensation strategy is effective to...