基于开放式控制器的铣削颤振在线抑制

为实现在线抑制铣削颤振,对颤振领域常用的传感器监控技术,尤其是三向切削力和振动加速度传感器的各向分量在颤振监控过程中的时域和频域敏感信号特征进行试验研究。针对监控的颤振敏感信号频域特性,研究快速傅里叶变换技术对信号有效信息的在线提取技术。对自激颤振的机理进行分析,建立颤振频率与主轴转速间的关系模型,为实现变主轴转速抑制自激颤振提供理论基础。对集成在线参数采集、反馈控制的全软件型模块化铣削控制器进行设计,将在线抑制颤振的相关变主轴转速算法嵌入开放式控制器中,并设计控制参数数据流在控制器模块间的实现流程。对连续变切削深度铝合金工件进行在线颤振抑制加工试验,试验验证开放式智能铣削控制器在线抑制颤振相关技术的正确性。     

Integration of cutting force control and chatter suppression control into automatic cutting feed adjustment system design

Abstract

This study designed an automatic cutting feed adjustment system for computer numerical control (CNC) turning machine tools, which integrate the operational characteristics of cutting force control and chatter suppression control to shorten the machining time and maintain the quality of workpieces. The setting of appropriate machining conditions (such as cutting feed, spindle speed and depth of cut) to consider both machining quality and efficiency often causes difficulties for machine tool operators. Therefore, this study uses cutting force control to design an automatic cutting feed adjustment method for cutting tools, and then, the chatter suppression control design is used to modify the cutting force command to suppress cutting chatter. The experimental results of the CNC turning machine tool show that the use of the cutting force control to adjust the cutting feed can shorten the machining time; however, the cutting chatter results in larger surface waviness on the workpiece surface. When the cutting force command is properly modified by actuating the chatter suppression control, the workpiece shows better surface roughness with prolonged machining time. Therefore, the cutting tests demonstrate that the proposed system is feasible for satisfying the machining requirements of the manufacturing processes of mechanical parts for high speed and high accuracy.     

Milling force vibration analysis in high-speed-milling titanium alloy using variable pitch angle mill

Chatter may cause fast wear of tools and poor surface quality of the workpieces at high cutting speed and it will happen on different process parameters; how do we select the suitable cutting speed to suppress the chatter? In this paper, a signal analysis method for milling force and acceleration is adopted to identify chatter, which can obtain the results not only in frequency of chatter but also in the contribution for milling force at different frequencies. Through the milling experiment, the machining vibration behaviors of milling Ti–6Al–4V with variable pitch end mill were investigated. Milling force and acceleration signals obtained from experiment were analyzed and compared at stable and unstable milling processes. The experimental results show that when the chatter occurs, milling forces were found to increase dramatically by 61.9–66.8% compared with that of at stable cutting; machining surface quality became poor and machined surface roughness increases by 34.2–40.5% compared with that of at stable cutting.     

Chatter prediction based on frequency domain solution in CNC pocket milling

Chatter has been a problem in CNC machining process especially during pocket milling process using an end mill with low stiffness. Since an iterative time-domain chatter solution consumes a computing time along tool paths, a fast chatter prediction algorithm for pocket milling process is required by machine shop-floor for detecting chatter prior to real machining process. This paper proposes the systematic solution based on integration of a stability law in frequency domain with geometric information of material removal for a given set of tool paths. The change of immersion angle and spindle speed determines the variation of the stable cutting depth along cornering cut path. This proposed solution transforms the milling stability theory toward the practical methodology for the stability prediction over the NC pocket milling.     

Chatter prevention for milling process by acoustic signal feedback

This paper presents how real-time chatter prevention can be realized by feedback of acoustic cutting signal, and the efficacy of the proposed adaptive spindle speed tuning algorithm is verified as well. The conventional approach to avoid chatter is to select a few appropriate operating points according to the stability lobes by experiments and then always use these preset cutting conditions. For most cases, the tremble measurement, obtained by accelerometers or dynamometers, is merely to monitor spindle vibration or detect the cutting force, respectively. In fact, these on-line measures can be more useful, instead of always being passive. Furthermore, most of these old-fashioned methodologies are invasive, expensive, and cumbersome at the milling stations. On the contrary, the acoustic cutting signal, which is fed into the data acquisition interface, Module DS1104 by dSPACE, so that an active feedback loop for spindle speed compensation can be easily established in this research, is non-invasive, inexpensive, and convenient to facilitate. In this research, both the acoustic chatter signal index (ACSI) and spindle-speed compensation strategy (SSCS) are proposed to quantify the acoustic signal and compensate the spindle speed, respectively. By converting the acoustic feedback signal into ACSI, an appropriate spindle speed compensation rate (SSCR) can be determined by SSCS based on real-time chatter level. Accordingly, the compensation command, referred to as added-on voltage (AOV), is applied to actively tune the spindle motor speed. By employing commercial software MATLAB/Simulink and DS1104 interface module to implement the intelligent controller, the proposed chatter prevention algorithm is practically verified by intensive experiments. By inspection on the precision and quality of the workpiece surface after milling, the efficacy of the real-time chatter prevention strategy via acoustic signal feedback is further examined and definitely assured.     

基于电流变材料的车削切断颤振抑制研究

应用电流变材料的特殊性能——对电信号的快速响应能力和连续可变的阻尼，研制了一种智能切削颤振抑制结构(刀座刚度可变部分)，并将其附加在车床刀架上，建立了机床车副颤振实时监控系统，实现了机床车削切断过程的颤振抑制。实验结果表明，利用电流变材料智能切削颤振抑制结构可以对机床车削振动进行有效控制，刀具的振动幅值减小50％以上，且工件表面的加工质量有较大提高。     

基于故障数据库的高速铣削诊断的研究

通过对高速铣削过程中各种铣刀状态下采集的振动信号进行时域、频域分析,对比不同磨损程度刀具的振动信号,找出与刀具状态对应的信号特征。基于LabVIEW平台,开发出在线分析监测系统。由于铣削加工过程的复杂性以及监测系统中得到的特征数据结构复杂、种类繁多,因此将数据库技术应用于在线监测系统中,从而实现对监测系统中数据有效集中管理,提高系统的即时反应速度和运行效率,实现对刀具状态的准确判断。     

一个应用于自动化加工系统的综合刀具监测系统

对于自动化加工系统、刀具破损和异常磨损的有效实时监测是一个亟待解决的问题。本文用声发射信号监测加工中心上各种刀具的破损、折损,针对多种工序、多咱切削条件的复杂情况,进行了可变参数的模式识别算法的研究。基于这个算法,开发了一个综合刀具破损监测系统。这个系统针对自动化加工基本单元——加工中心的车、镗、铣多种工序,使得自动化加工系统的综合监测成为可能。实验验证表明,识别成功率大于90%。     

复杂曲面加工过程中铣刀在线监测方法

在验证了铣削力与刀柄摆动电涡流位移信号之间存在线性关系的基础上,以机床主轴端部x,y方向的加速度信号二次频域积分结果作为刀柄摆动位移信号,提取积分位移信号的基频及其谐波信号作为监测信号,解决了电涡流位移传感器安装不便的问题,同时有效去除了干扰信号的影响。利用时域同步平均(time synchronous averaging,简称TSA)计算监测信号的一阶和二阶累积量,结合时域指标方差、偏斜度、峭度、绝对均值及有效值定量刻画累积量波形,通过设定阈值实现状态预警,较好地解决了复杂曲面加工过程中铣刀状态在线监测与预警的难题。     

基于模态区间的数控机床切削状态监测

随着高速高精数控加工技术的发展,对数控机床切削加工状态的稳定性提出了更高的要求,传统的切削加工状态监测方法中对不确定性处理存在不足。提出了一个基于模态区间的切削状态监测不确定性处理方法,利用模态区间的宽度对传统监测方法中的不确定性加以表述,以解决监测中的不确定性问题。为了验证提出方法的有效性,搭建了切削加工实验平台,通过加速度传感器获取数控机床切削加工信息,由时频分析方法将切削状态划分成稳定、过渡及颤振3个加工阶段,利用基于模态区间的小波包能量百分比方法,提取不同加工阶段的区间特征量,通过Lloyd算法进行编码后作为基于模态区间的广义隐马尔科夫模型的输入特征向量,最后利用广义隐马尔科夫状态辨识方法,对数据机床切削状态进行了识别。实验结果表明,基于模态区间的广义隐马尔科夫模型辨识方法优于传统的隐马尔科夫模型辨识方法。     

Identifying bifurcation behavior during machining process for an irregular milling tool geometry

High-productivity machining processes cause tool and material defects and even damages in machine spindles. The onset of self-excited vibration, known as chatter, limits this high material removal rate. This chatter vibration refers to machining instability during cutting processes, which results in bifurcation behavior or nonlinear effect wherein the tool and the workpiece are not engaged with each other. In particular, bifurcation for low-radial immersion conditions can be easily promoted and identified. In this study, an experiment on an irregular milling tool as a variable helix and variable pitch geometry was conducted under a flexible workpiece condition. The bifurcation behavior from regenerative chatter was identified and quantified from displacement sensor and inductive sensor measurements. A series of cutting tests was used to measure the vibration signals, which were then analyzed based on the frequency spectrum, the one-per-revolution effect, and the Poincaré section. According to results, Hopf bifurcation and period-one bifurcation instabilities apparently occurred to validate chatter stability prediction through a semi-discretization method. However, period-doubling bifurcation was only determined during the unstable cutting of a uniform tool that was not in variable helix/pitch or an irregular milling tool. An irregular tool geometry caused the modulation of the regenerative effect to suppress chatter, and period-doubling instability could not be exhibited during cutting as a regular tool behavior. This period-one chatter instability of an irregular milling tool should be identified and avoided by practitioners to achieve high productivity in machining using the aforementioned irregular milling tools.     

基于音圈电机作动器的主轴振动LQG控制研究

为克服被动动力吸振器偏离最优状态时抑振效果严重降低的不足,针对动刚度较低的铣削加工机床的主轴振动控制,设计了一种混合动力吸振器的主动振动控制系统。该吸振器以音圈电机为作动器,以位移和速度作为状态反馈信号,直接对铣削刀具施加控制力,从而达到抑制主轴振动的目的。在分析音圈电机驱动特性的基础上,建立了两自由度的铣刀与主轴振动力学模型,推导出系统的状态方程,并采用线性二次高斯控制（LQG）最优控制方法对振动控制模型进行了仿真,最后在实际的数控雕铣机床上进行了相关的铣削主轴振动控制实验。结果表明,该方法能有效降低主轴切削振动,基于振动位移反馈的抑振效果优于基于振动速度反馈的抑振效果,但基于振动速度反馈能更有效地抑制高频的共振峰值,实际系统应根据振动反馈信号实时调整主动控制参数。     

Proposal of novel spindle speed variation profile with constant acceleration rate for improvement of chatter stability

Spindle speed variation (SSV) is one of the effective methods which suppresses regenerative chatter. However, regenerative chatter can grow even if SSV is applied. In the previous work, the chatter growth characteristics in SSV were clarified. The chatter frequency changes proportionally to the varying spindle speed, and it causes the change of the magnitude of the dynamic compliance. Hence, chatter can be suppressed through SSV since the dynamic compliance usually reduces as the chatter frequency changes. A greater compliance reduction can be obtained by a higher rate of spindle speeds in two consecutive revolutions at the same angular position, i.e., acceleration rate. From the investigations in the previous work, limitation of the conventionally utilized SSV profiles is found as follows: the acceleration rate always fluctuates with speed variation and the chatter vibration grows where the acceleration rate is insufficient for suppression, and hence suppressing chatter in all sections of SSV is difficult. In this paper, a new SSV profile with a constant acceleration rate, namely CAR-SSV, is proposed to overcome the limitation of chatter stability improvement by utilizing conventional SSV profiles. The magnitude of the acceleration rate is kept constant to realize the chatter suppression effect throughout the cutting process. Through time-domain simulation and cutting experiments, the chatter stability of CAR-SSV is investigated based on the previously introduced chatter stability evaluation indices. Influence of the parameters of CAR-SSV on the stability is investigated, and an appropriate strategy for setting SSV parameters to achieve higher stability is discussed. In addition, in order to verify the effectiveness of the proposed profile, the stabilities of conventional SSV profiles and CAR-SSV are compared through time-domain simulations and cutting experiments.     

APPLICATION OF WAVELET TRANSFORM ON DIAGNOSIS AND PREDICTION OF MILLING CHATTER

In order to avoid the accuracy deterioration or tool damage caused by milling chatter, it is necessary to have an efficient and reliable diagnosis system that can on-line predict/detect the occur-rence of chatter. The diagnosis/predicting system proposed is to on-line process and analysis the vi-bration signals of the milling machine measured by accelerometers. According to the analysis results, the system will be able to detect/predict the occurrence of the chatter. The diagnosis algorithm is, first, collecting both the normal signals and chatter signals from milling processes, and then, converting the signals through wavelet transform and fast Fourier transform (FFT). Since the converted chatter sig-nals exhibit different characteristics from the normal signals, through defining the characteristic val-ues, such as root-mean-square value, max value, and ratio of peak value to root-mean-square value, etc, a diagnosis reference library that contains the distribution of these characteristic values is built for diagnosis. When a diagnosis is executing, the characteristic value of the measured signals is con-trasted with the diagnosis reference. The approach index which shows the possibility of occurrence of milling chatter will, then, be calculated through the diagnosis system. Cutting experiments are con-ducted to verify the proposed diagnosis system. The results show the success of early chatter detecting for the system.     

Chatter vibration surveillance by the optimal-linear spindle speed control

The paper concerns self-excited chatter vibration during high speed slender ball-end milling. Non-stationary cutting process, with inclusion of various approaches towards dynamic characteristics of the process, is described. Dynamic analysis of the milling process is performed and dynamics of controlled closed loop system with time-delay is presented. In order to reduce vibration level, instantaneous change in the spindle speed appears as a control command, and thus—the method of vibration surveillance by the spindle speed optimal-linear control is developed. Presented cutting models have been applied for the proposed method and procedure of the chatter vibration surveillance with a use of variable spindle speed has been developed. Computer simulations are performed for selected cases of ball-end milling at constant and variable spindle speed. The results of them are successfully confirmed by experimental investigations on the Alcera Gambin 120CR milling machine equipped with the S2M high speed electrospindle.     

Intelligent monitoring and prediction of tool wear in CNC turning by utilizing wavelet transform

In order to realize an intelligent CNC machine, this research proposed the in-process tool wear monitoring system regardless of the chip formation in CNC turning by utilizing the wavelet transform. The in-process prediction model of tool wear is developed during the CNC turning process. The relations of the cutting speed, the feed rate, the depth of cut, the decomposed cutting forces, and the tool wear are investigated. The Daubechies wavelet transform is used to differentiate the tool wear signals from the noise and broken chip signals. The decomposed cutting force ratio is utilized to eliminate the effects of cutting conditions by taking ratio of the average variances of the decomposed feed force to that of decomposed main force on the fifth level of wavelet transform. The tool wear prediction model consists of the decomposed cutting force ratio, the cutting speed, the depth of cut, and the feed rate, which is developed based on the exponential function. The new cutting tests are performed to ensure the reliability of the tool wear prediction model. The experimental results showed that as the cutting speed, the feed rate, and the depth of cut increase, the main cutting force also increases which affects in the escalating amount of tool wear. It has been proved that the proposed system can be used to separate the chip formation signals and predict the tool wear by utilizing wavelet transform even though the cutting conditions are changed.     

Hybrid model- and signal-based chatter detection in the milling process

Chatter causes machining instability and reduces productivity in the metal cutting process. It has negative effects on the surface finish, dimensional accuracy, tool life and machine life. Chatter identification is therefore necessary to control, prevent, or eliminate chatter and to determine the stable machining condition. Previous studies of chatter detection used either model-based or signal-based methods, and each of them has its drawback. Model-based methods use cutting dynamics to develop stability lobe diagram to predict the occurrence of chatter, but the off-line stability estimation couldn’t detect chatter in real time. Signal-based methods apply mostly Fourier analysis to the cutting or vibration signals to identify chatter, but they are heuristic methods and do not consider the cutting dynamics. In this study, the model-based and signal-based chatter detection methods were thoroughly investigated. As a result, a hybrid model- and signal-based chatter detection method was proposed. By analyzing the residual between the force measurement and the output of the cutting force model, milling chatter could be detected and identified efficiently during the milling process.

     

超磁致伸缩致动器抑制车削加工颤振实验研究

切削颤振会降低加工质量与切削效率,降低刀具、机床的使用寿命,超磁致伸缩致动器是利用稀土-铁超磁致伸缩材料Terfenol-D在外加磁场作用下发生形变这一特性,实现电磁能向机械能转换的一种新型转换器。笔者建立以超磁致伸缩致动器为执行元件的微位移刀架切削系统,通过给微位移刀架加振动切削信号,实验研究抑制切削颤振。     

铣削加工测力刀柄参数优化设计研究

为适应高精密加工对切削力的监测需求,文中面向铣削加工设计了一种无线测力刀柄,使用压电薄膜和弹性检测梁采集力信号。为提高检测信号的灵敏度,基于COMSOL Multiphysics软件使用Nelder-Mead算法对刀柄的结构参数进行优化设计,并通过有限元仿真对优化结构进行刀柄结构刚度校核和动态特性分析,最后进行铣削对比实验,验证设计方案的可行性。结果表明,文中设计和优化的测力刀柄具有良好的灵敏度,刀柄的动静态特性满足使用需求,是一种有效的切削力监测方案。