Research On Regenerative Chatter On-line Detection Method And Application

Regenerative chatter is a kind of self-excited vibration acting between the machine tool and the workpiece,it will affect the machining quality and machining efficiency,even to destroy the machining system.Therefore,online detection of early chatter is a necessary prerequisite for active chatter control.This thesis aims to detect the early chatter in order to achieve the online detection goal,the thesis first study the causes and development characteristics of chatter through regenerative chatter theory and dynamics simulation,then an online detection method for regenerative chatter is established.The method can identify chatter frequency at the same time track the development trend of the chatter amplitude,moreover it can send the chatter alarm through the low signal-to-noise ratio vibration signal in case of the chatter frequency is unknown.The main work of thesis includes:(1)The formation mechanism and simulation signal characteristics of regenerative chatter and regenerative modulated chatter are studied.A dynamic cutting force model was established based on the regenerative chatter theory and the single-degree-of-freedom mechanical vibration theory.Based on this model,the cutting process was simulated by Simulink,and the simulated vibration signal characteristics under different cutting parameters(cutting width)were obtained.Furthermore,the workpiece eccentricity factor is introduced into the model.Compared with the normal regenerative chatter,the frequency amplitude of the regenerative modulated chatter is no longer monotonously increasing during the development process,but exhibits fluctuations modulated by the rotational frequency of the workpiece.Therefore,this thesis also performed Simulink simulations of regenerative modulated chatter under different cutting widths,and probe the signal characteristics of regenerative modulated chatter and regenerative modulated chatter.(2)The online detection method for regenerative chatter has been established.According to the monotonic increase of the chatter amplitude,the online detection method of regenerative chatter is studied.The method uses short-time Fourier transform processing to reflect changes in the amplitude of each component,and uses the difference spectrum method to screen the components that the amplitude increases with time.On this basis,the monotonicity judgment method is used to judge each component which carried out by difference spectrum,and adaptively identify the chatter that the amplitude increasing monotonously.At the same time,the performance of the short-time difference spectrum method is verified by the wheel-to-axle cutting experiment and the simulation signal.The experimental results show that the short-time difference spectrum method(STDSA)can identify the chatter frequency from the low signalto-noise ratio vibration signal and track the development trend of chatter amplitude,which provides an effective early warning for chatter in the early stage of chatter development.This thesis also uses the variational modal decomposition energy entropy(VMD-EE)algorithm to process the simulation and experimental signals.The results show that the STDSA method can identify chatter characteristics in the case of low signal-to-noise ratio,while the VMD-EE method cannot;the STDSA method can accurately identify the chatter frequency,and the VMDEE method can only determine the moment when the chatter occurs.(3)The online detection method for regenerative modulated chatter has been established.According to the signal characteristics of regenerative modulated chatter,this thesis proposes the moving average difference spectrum method(MADSA)based on the research of the STDSA method.The method introduces moving average processing to eliminate the fluctuations in the chatter amplitude which caused by the eccentricity of the workpiece or the beat frequency effect.At the same time,the chatter amplitude value trend between adjacent extreme points has been proposed for the moving average parameter.The distance is used as an adaptive parameter selection method of sliding length to ensure the online detection ability of the algorithm.The accuracy of the algorithm is verified through experimental signals and simulation signals.The experimental detection results show that the MADSA method can issue an early warning in the chatter development stage and give the chatter amplitude trend after eliminating the influence of fluctuations.However,compared with the online detection results of regenerative chatter,the early warning time of the regenerative modulated chatter detection algorithm inevitably lags because of the modulated influence.In this thesis,the wavelet packet energy entropy(WP-EE)method is used to process the simulation and experimental signals.The results show that compared to the MADSA method,the index(energy entropy value)of the WP-EE algorithm repeatedly crosses the threshold which causing false alarming,and lose the effective warning of the regenerative modulated chatter.