Real-time Monitoring And Control For Chatter And Deflection Of Thin-walled Parts In Flank Milling

With rapid development of the field of aeronautics and astronautics,thin-walled parts are widely used in engineering field.Because of its poor rigidity,chatter and cutting deflection are easy to occur in the cutting process.Through analyzing the imformation of cutting process collected by sensors,cutting parameters can be optimized by cutting process control,and suppression of chatter and deflection of thin-walled part can be effectively implemented.According to the difference of control strategies and implementation methods,cutting process control can be divided into off-line control,online control and real-time control.In three kinds of control mode,real-time control of cutting process could collect and processing sensor information in the cutting process.At the same time,cutting parameters could be optimizd by the corresponding control strategy.Integration and implementation of chatter suppression and deflection control in smart CNC system are researched in this dissertation,and finally real-time monitoring of chatter and cutting deflection for aluminum alloy thin-walled part will be realized based on the method of real-time control of cutting process.To realize real-time chatter identification in flank milling of thin-walled parts,the model of chatter identification is established based on hidden markov model(HMM)in this dissertation.It is need to estimate the signal frequency through the algorithm of “Estimating Signal Parameters via Rotational Invariant Technique(ESPRIT)”,then the cutting process could be divided into stable cutting state,marginal chatter state,and chatter state based on the amplitude-frequency characteristics of signals.Using the signals with category labels as samples to train HMM's state transition matrix and confusion matrix,and then the model parameters of chatter identification could be obtained.The model of chatter identification is integrated into monitor controller,and real-time chatter identification system which has viberation signals input and cutting state output is established.This system can directly process vibration signals by identification model,and realize identification of chatter and different cutting state in the cutting process.After chatter identification,it is need to suppress chatter immediately to ensure the stability of cutting process.Empirical model between cutting force and spindle speed is established based on signal factor experiment and orthogonal experiment under different cutting conditions,then chatter suppression strategy of spindle speed variation is determined which have inputs of cutting force error and error change rate and output of spindle speed variation based on fuzzy control algorithm.To realize real-time chatter suppression,the strategy of chatter suppression which has the mode of separate thread need to be integrated into system coordinate module of smart CNC system,and varified spindle speed will be output by this thread.After establish data interaction mechanism between chatter identification system and smart CNC system,spindle speed could be adjusted by smart CNC system based on collected cutting force signals and output cutting state signals in the cutting process,then real-time chatter suppression in flank milling of thin-walled parts could be realized.Chatter suppression could improve the surface finish of the part,deflection control could improve the machining accuracy.To effectively control cutting deflection in flank milling of thin-walled parts,the strategy of cutting deflection control is proposed in this dissertation based on the numerical model of cutting deflection and real-time feedrate optimization.According to simulation results of thin-walled parts milling,the numerical model among feedrate of machine tool,cutting force and cutting deflection is established,and optimal cutting force is determined to control deflection by this model.In the platform of smart CNC system with open modular,the function of real-time acquisition and processing of cutting force signals,and real-time feedrate optimization strategy which based on Brent-Dekker algorithm are developed.In flank milling of thin-walled parts,according to measured cutting force and the algorithm of feedrate optimization,cutting force is gradually close to the optimal value by adjusting feedrate of mahine tool in realtime,thus balance and optimization control of cutting deflection and machining efficiency are realized.Finally,experimental verification of chatter and deflection contrl are implemented respectively.For the experiment of real-time chatter monitoring,spindle speed of machine tool could be adjusted in real-time by smart CNC system based on integrated smart control algorithm.Chatter could be suppressed in the marginal chatter state,and surface quality of the part is improved.For the experiment of cutting deflection control,cutting force could be controlled under a specific range by smart CNC system based on determined maximum value of cutting deflection,and machining efficiency could be improved under the condition of dimensional tolerance.Furthermore,real-time comprehensive control of chatter and deflection is researched in this dissertation.According to the established strategy of comprehensive control,aluminum alloy thinwalled part which has small-curvature surface is selected as the experimental samples,and the effectiveness of comprehensive control function of smart CNC system is verified.