离散隐马尔可夫模型在颤振预报中的应用研究

对于切削过程中颤振孕育的动态模式,提出了基于离散隐马尔可夫模型(DHMM)的模式识别理论预报颤振的新方法。首先对切削过程的振动信号进行FFT特征提取,然后利用自组织特征映射(SOM)神经网络对提取的特征矢量进行冗余信息压缩与预分类编码;再根据多变量DHMM建模理论,对切削颤振孕育的各种过程模式建立相应的DHMM,把矢量编码作为观测序列引入到DHMM中进行机器学习、训练;最后将观测序列引入到DHMM中进行颤振孕育的概率识别尝试。实验表明,该方法对颤振孕育过程识别是十分有效的,颤振预报正确率达93.3%。     

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.     

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.

     

Unique regenerative chatter in wiper-turning operation with burnishing process Part 1: Prediction and analytical investigation of generation mechanism,critical stability,and characteristics

The purpose of this paper is to understand the generation mechanism and to propose an analytical model of a unique regenerative chatter with the burnishing process in wiper-turning operations. The authors have found a unique chatter when using wiper inserts, which cannot be explained by the existing chatter theory found in the literature. The authors believe that this occurs because of the burnishing process of the wiper insert, which is the only difference from ordinary turning. At first, the burnishing process, which accompanies wiper inserts, is explained, and the turning operation with this process and the well-known regenerative effect in the cutting process is discussed. Then, the stability of the turning process with the regenerative effects in the cutting and burnishing processes are investigated, and an analytical model is proposed to evaluate the critical stability. Finally, the stability analysis of this unique chatter is conducted, and its generation mechanism and characteristics are examined clearly.     

微小型无偏正交车铣加工系统稳定性研究

以微小型车铣复合加工系统为对象,通过对微小型车铣加工工艺系统进行分析将其简化为进行端铣研究。针对加工系统中刚度最低的工件系统利用再生型颤振理论进行分析,得到加工稳定性叶瓣图,并且通过实验验证了该叶瓣图的准确性。得到的微小型车铣稳定性叶瓣图可以指导微小型车铣的加工参数选择,提高微小型车铣加工效率。     

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).     

TIME SERIES ANALYSIS IN METAL CUTTING: CHATTER VERSUS CHATTER-FREE CUTTING

Time series of cutting force under two different regimes of turning on a lathe were analysed. With an increase of cutting depth the cutting regime was changed from chatter-free cutting to one with chatter. Using three different surrogate data tests, the dynamics of chatter-free cutting were found to be consistent with a linearly correlated random process, whereas the dynamics of chatter could be explained by a low-dimensional, presumably weakly chaotic process. The differences in the dynamics of the two cutting regimes were exploited successfully for the purpose of chatter detection.     

Chatter and dynamic cutting force prediction in high-speed ball end milling

Machine tool chatter is a serious problem which deteriorates surface quality of machined parts and increases tool wear, noise, and even causes tool failure. In the present paper, machine tool chatter has been studied and a stability lobe diagram (SLD) has been developed for a two degrees of freedom system to identify stable and unstable zones using zeroth order approximation method. A dynamic cutting force model has been modeled in tangential and radial directions using regenerative uncut chip thickness. Uncut chip thickness has been modeled using trochoidal path traced by the cutting edge of the tool. Dynamic cutting force coefficients have been determined based on the average force method. Several experiments have been performed at different feed rates and axial depths of cut to determine the dynamic cutting force coefficients and have been used for predicting SLD. Several other experiments have been performed to validate the feasibility and effectiveness of the developed SLD. It is found that the proposed method is quite efficient in predicting the SLD. The cutting forces in stable and unstable cutting zone are in well agreement with the experimental cutting forces.     

基于小波包能谱熵的铣削颤振监测方法

针对切削加工过程中容易出现颤振,导致零件表面加工质量降低,本文以铣削加工为研究对象,提出了基于小波包能谱熵的铣削颤振监测方法。信号的采集是一个连续的过程,为避免刀具不参与切削对这种方法的影响,本文提出基于铣削力幅值平方和的方法以识别刀具是否参与切削。试验结果表明,无论对于刀具是否参与切削的识别或者是否出现铣削颤振的监测都能有效的监测。     

Analysis of regenerative chatter suppression with adding the ultrasonic elliptical vibration on the cutting tool

A method is proposed to suppress regenerative chatter in turning operation, in which the ultrasonic elliptical vibration is added on the cutting tool. It results in the fact that the cutting tool is separated periodically from the chip and the workpiece, and the direction of the frictional force between the rake face of the cutting tool and the chip is reversed in each cycle of the ultrasonic elliptical vibration. The experimental investigations show that the regenerative chatter occurring in ordinary turning operation can be suppressed effectively by applying the ultrasonic elliptical vibration on the cutting tool. In order to clearify the reason of the regenerative chatter suppression, theoretical analysis and computer simulation are performed on turning with ultrasonic vibration. There is a good agreement among the experimental investigations, theoretical analysis and the computer simulation.     

ESPRIT- and HMM-based real-time monitoring and suppression of machining chatter in smart CNC milling system

Suppression of machining chatter during milling processes is of great significance for surface finish and tool life. In this paper, a smart CNC milling system integrating the function of signal processing, monitoring, and intelligent control is presented with the aim of real-time chatter monitoring and suppression. The algorithm of estimation of signal parameters via rotational invariance techniques (ESPRIT) is adopted to extract the frequency characteristics of acceleration signals, and then, cutting state is categorized as stable state, chatter germination state, and chatter state based on amplitude-frequency characteristics of identified acceleration signals. The model of chatter identification is acquired by training a hidden Markov model (HMM), which combines acceleration signals and labeled cutting state. To implement real-time chatter suppression, the algorithm of fuzzy control is integrated into a smart CNC kernel to determine the relationship between cutting force and spindle speed. Furthermore, spindle speed of machine tool could be adjusted timely in the presented system once the chatter is identified. Finally, the effectiveness of the proposed real-time chatter monitoring and suppression system is experimentally validated.     

有限样本下基于迁移学习的铣削稳定性预测方法

传统铣削稳定性分析因采用静态刀尖点频响函数和平均切削力系数而使其在真实工况下的预测精度降低。为此,引入迁移学习提出一种基于少量实验样本的铣削稳定性预测方法。首先,生成静态刀尖点频响函数和平均切削力系数在全转速范围内多个系列的随机值,并在各系列下进行铣削稳定性分析,通过计算少量极限切削深度实验值与对应的预测值之间的误差,确定最优系列并以其构造源域稳定域数据;然后,利用大量源域数据建立极限切削深度的预训练模型,通过少量实验样本全局微调此模型使其适应真实加工场景。以40组颤振实验样本展开实例验证,所提方法比采用少样本建模的预测精度提升32%,并对比不同数据规模下各类模型预测精度,共同验证所提方法的有效性。     

Prediction of regenerative chatter in the high-speed vertical milling of thin-walled workpiece made of titanium alloy

With the wide application of high-speed cutting technology, high-speed machining approach of titanium alloy has become one of the most effective ways to improve processing efficiency and to reduce the processing cost, but the cutting chatter which often occurs in the cutting process not only affects the machining surface quality but also reduces the production efficiency. Regenerative chatter is a typical phenomenon during actual cutting, and it has the greatest impact on the cutting process. With the purpose of avoiding regenerative chatter and selecting appropriate cutting parameters to achieve a steady cutting process and a high surface quality, it is necessary to determine the critical boundary conditions where chatter occurs. Built on the work of previous theoretical researches of regenerative chatter, this paper utilized Visual C++ software to calculate the chatter stability domain during the finish machining of titanium alloy. It was shown that the border between a stable cut and an unstable cut can be visualized in terms of the axial depth of cut as a function of the spindle speed. Using the result, it can find the specific combination of machining parameters, which lead to the maximum chatter-free material removal rate. In order to verify the result, the high-speed milling experiment of an I-shaped thin-walled workpiece made of titanium alloy was conducted. It revealed that the actual machining result was consistent with the calculation prediction. This study will offer a useful guide for effective parameter selection in future CNC machining applications.     

颤振征兆早期识别的模糊信息融合法

基于切削试验探讨颤振征兆早期识别的模糊信息融合方法。试验中在同一个测量区内使用了功率传感器和加速度传感器,利用模糊数学与Dempster-Shafer证据论相结合的方法对两种传感器信息进行了分析融合,对切削状态进行了描述。试验证实:利用证据理论与模糊推理相结合的信息融合方法进行颤振征兆的早期模糊识别得出的目标切削状态的隶属度介于单一征兆隶属度之间,对过于敏感的传感器,会考虑其他传感器的信息予以修正,降低其评价隶属度;对于不敏感传感器,会考虑其他传感器的信息予以补偿。这种方法弥补了最大隶属度原则的缺陷,即在模糊推理中,系统对某一状态的隶属程度实际上是由模式特征集中贡献最大的那个特征决定的,而没有用到其他特征提供的信息,这说明证据理论与模糊推理相结合的信息融合方法在进行颤振征兆早期识别时具有更高的可靠度。     

Automatic selection of spindle speed for suppression of regenerative chatter in turning

The paper presents a new spindle speed regulation method to avoid regenerative chatter in turning operations. It is not necessary to analyse complex cutting dynamics to search for stable spindle speeds to eliminate regenerative chatter. The metal removal rate is also greatly improved by using this method. The stability lobe diagram for the stability limit of chip width and chatter frequency versus spindle speed is derived by using the Nyquist stability criterion. It is shown that stable spindle speeds can be automatically obtained when the chatter frequency is found. Computational simulations and experimental cutting tests are performed to illustrate the proposed method.     

DHMM＋SVM在切削颤振中的应用

根据切削颤振的特点,结合隐马尔可夫模型（Hidden Markov Model,HMM）和支持向量机（Support Vector Machine,SVM）的特点,提出了一种新的状态预测技术,同时也提出了一种新的特征提取方法。首先在等时间间隔内对切削信号实时进行小波包分解,然后通过SVM对各频带区间能量变化趋势进行回归预测,最后通过HMM对预测结果进行分类。结果表明,该方法取得了较好的预测结果。     

再生振动和刀具偏心对立铣加工精度综合影响的研究

基于再生振动和刀具偏心对立铣加工过程的影响,建立了改进的动态切削力和切削厚度的非线性数学模型;利用计算机仿真技术,定量分析了上述因素对铣削加工振动和工件三维表面形貌的综合影响。结果表明:考虑再生振动和刀具偏心的综合影响,可使铣削振动的预测精度较未考虑这两个因素时平均提高20%以上,使加工振动状态更接近实际加工情况。     

Unique regenerative chatter in wiper-turning operation with burnishing process Part 2: Experimental verification of predicted generation mechanism,critical stability,and characteristics

In this paper, the predicted generation mechanism, chatter stability, and characteristics of the unique regenerative chatter with the burnishing process in wiper-turning operations are verified experimentally. It was found in the first part of the paper that the vibration regenerates in the burnishing process by the wiper part of the insert causing a novel type of chatter. In this second part, this chatter phenomenon is investigated in an experimental manner to verify its mechanism. The specific burnishing force, which is a gain factor characterizing the burnishing process, is determined by the Hertzian contact law. In addition, the specific cutting force is measured by a cutting test, the compliance of the flexible structure is measured by a hammering test, and the residual compliance is measured by a static indentation test. Then, experiments are conducted where the tilt angle and the feed rate are varied to find the critical stability. The conducted chatter experiments prove that the predicted generation mechanism, critical stability, and characteristics are true.     

基于支持向量机的颤振在线智能检测

为了检测车削过程中的颤振,提出一种颤振在线智能检测方法。使用最小二乘一类支持向量机,训练出描述特征矢量集的超球面,通过计算被测样本与超球面的距离来判断其是否颤振。基于相干准则和分块矩阵求逆,构造了在线稀疏结构的最小二乘一类支持向量机,将特征信息存储于特征库(字典)中,通过更新特征库实现检测模型的在线进化。在颤振检测的应用中,首先使用小波包分解,得到第三层节点能量的比例作为特征矢量,以离线数据构造特征矢量作为输入,训练得到初始检测模型以及特征库,在线检测中不断更新特征库,实现检测模型的在线进化。试验结果表明,在车削颤振识别中,在线进化的检测模型的识别效果更好,颤振预报准确率高达至99.04%,优于离线模型的预报准确率96.74%。     

Chatter detection by monitoring spindle drive current

The purpose of this work is to investigate a new method for detecting chatter in milling. In this method, the spindle drive current signal of a vertical milling machine is used for monitoring process instability. Both simulations and experimental work are conducted. Results show that current signals can transmit chatter frequencies reliably. The sensitivity of the current signal to slight process instability is assessed. A statistical indicator, the R-value is used to evaluate this sensitivity. Statistical analysis of experimental data shows that the R-value is insensitive to variations in speed, feed and geometry of cut. Also, experiments show that slight variations in the process instability results in a significant increase in the R-value.