机床圆柱结合部的动态特性解析方法

在机床图纸设计阶段，预测机床整机的动态特性具有十分重要的意义，进行机床整机动态特性预测的难点在于如何确定结合部的刚度和阻尼参数，本文以机床结构中应用较普遍的圆柱结合部为例，研究了基于结合面基础特性参数的圆柱结合部动态特性解析方法，并编制相应解析软件，给出应用实例，证明本文的方法及软件是正确的。     

Estimation of machine-tool dynamic parameters during machining operation through operational modal analysis

The stability of high-speed machining operations determines the reliability of machine tools and the quality of machined parts. Chatter-free cutting conditions are difficult to predict as they require accurately estimated dynamic modal parameters. A spectrogram analysis and impact tests for different configurations of the machine tools were conducted to compare the modal parameters at 0 rpm tests and during machining tests. Variations of between 2% and 8% were observed for the natural frequencies and between 2 and 10 times for the damping ratios.The operational modal analysis (OMA) is considered as a powerful tool for dynamic modal parameter estimations during machining operations. A complete methodology for applying this technique for machining operations was detailed. It was demonstrate how the OMA can be industrially exploited. The proposed approach was successfully applied during the high-speed machining of the 7075-T6 aluminum alloy to extract machine-tool parameters. Two different numerical approaches were used: the autoregressive moving average method (ARMA) and the least square complex exponential method (LSCE), both of which generated similar results. The dynamic parameters found using the operational modal analysis were used to predict machine dynamic stability lobes, and through experimental validation, it was shown that some depths of cut that are stable with standard stability lobes become unstable with dynamic stability lobes.     

Complex form machining with axis drive predictive control

The paper proposes implementation of predictive control strategies on an industrial machining centre dedicated to high speed machining, realized within the framework of a CETIM study. Modelling, parameters identification and performances of the robustified axes drive polynomial controllers are first validated within a virtual machine-tool environment. Implementation is then achieved on the AXELOR 20SL machining centre, equipped with a Power Automation CNC. The computation of the controllers is carried out through the concept of compile cycles for real time scheduling. Results obtained with predictive control when machining a complex workpiece are finally compared to those achieved with the classical CNC control architecture.     

Tool point dynamics prediction by a three-component model utilizing distributed joint interfaces

In machine dynamics the tool point frequency response functions (FRFs) are employed to predict the stable machining conditions. In this paper, a combined analytical–experimental substructuring procedure is proposed to determine the tool point FRFs for different holder–tool configurations. The method employs the measured spindle-machine FRFs and analytical models of the tool and the holder to predict the tool tip FRFs for different sets of tools and holders mounted on the machine spindle without the need for repeated experimental measurements. Distributed joint interfaces are used to couple the three-component model of the machine. The machine tool tip FRFs with different tool–holder combinations are obtained assuming the clamping conditions at joint interfaces remain unchanged. An experimental case study is provided to demonstrate the applicability of the proposed method in dynamic modeling of machine tool.     

Prediction of chatter in NC machining based on a dynamic cutting force model for ball end milling

Ball end milling is one of the most widely used cutting processes in the automotive, aerospace, die/mold, and machine parts industries, and the chatter generated under unsuitable cutting conditions is an extremely serious problem as it causes excessive tool wear, noise, tool breakage, and deterioration of the surface quality. Due to the critical nature of detecting and preventing chatter, we propose a dynamic cutting force model for ball end milling that can precisely predict the cutting force for both stable and unstable cutting states because our uncut chip thickness model considers the back-side cutting effect in unstable cutting states. Furthermore, the dynamic cutting force model considers both tool runout and the penetration effect to improve the accuracy of its predictions. We developed software for calculating the cutting configuration and predicting the dynamic cutting force in general NC machining as well as single-path cutting. The chatter in ball end milling can be detected from the calculated cutting forces and their frequency spectra. A comparison of the predicted and measured cutting forces demonstrated that the proposed method provides accurate results.     

一种用于大长径比铣刀杆减振的新型动力减振器

针对大长径比铣刀杆刚性差、加工中极易出现切削颤振的特点,提出一种新型动力减振装置。设计了铣刀杆整体结构,建立了减振铣削系统的铣削动力学模型。运用机械振动学和动力减振的定点理论推导出最优频率比和最佳阻尼比公式,利用MATLAB软件验证所建立模型的准确性;计算出减振装置的最优参数,进行动力减振器的结构设计;通过ADAMS软件进行了仿真实验,验证所设计的减振装置的减振效果,同时进行了实际的切削实验。结果表明:所设计的减振装置具有很好的减振效果。     

基于ANSYS的重型机床-基础系统动态特性分析

重型机床的动态特性主要受结合面和基础的影响,其性能直接关系到工件的加工精度。采用分形理论建立结合面节点刚度模型,通过计算各节点压强值,从微观角度采用MATRIX27矩阵单元将节点刚度值导入宏观结合面中;然后建立了考虑结合面的重型机床-基础有限元模型,采用ANSYS对重型机床-基础系统振动模态及谐响应进行仿真分析;最后对比现场实验验证了模型的正确性。基于该模型研究了箱基轮廓尺寸对重型机床-基础系统动态特性的影响规律,通过上述模型能够验证重型机床-基础系统结构的合理程度,为进一步改进指出方向。     

高速电主轴单元-主轴箱体结合面模态分析与研究

为准确了解高速电主轴的动态特性、提高加工精度,利用ANSYS Workbench建立基于高速电主轴单元-主轴箱体结合面特性的有限元分析模型,又利用吉村允孝法确定结合面的刚度,而后对其进行模态分析和谐响应分析,得出其固有频率、振型和动刚度。最后采用锤击法试验验证,证明该分析方法的有效性,为产品设计分析提供理论依据。     

Estimation of CNC machine–tool dynamic parameters based on random cutting excitation through operational modal analysis

Dynamic properties of the whole machine tool structure including tool, spindle, and machine tool frame contribute greatly to the reliability of the machine tool in service and machining quality. However, they will change during operation compared with the results from static frequency response function measurements of classic experimental modal analysis. Therefore, an accurate estimation of the dynamic modal parameters of the whole structure is of great value in real time monitoring, active maintenance, and precise prediction of a stability lobes diagram.Operational modal analysis (OMA) developed from civil engineering works quite efficiently in modal parameters estimation of structure in operation under an intrinsic assumption of white noise excitation. This paper proposes a new methodology for applying this technique in the case of computer numerically controlled (CNC) machine tools during machining operations. A novel random excitation technique based on cutting is presented to meet the white noise excitation requirement. This technique is realized by interrupted cutting of a narrow workpiece step while spindle rotating randomly. The spindle rotation speed is automatically controlled by G-code part program, which contains a series of random speed values produced by MATLAB software following uniform distribution. The resulting cutting produces random pulses and excites the structure in all three directions. The effect of cutting parameters on the excitation frequency and energy was analyzed and simulated. The proposed technique was experimentally validated with two different OMA methods: the Stochastic Subspace Identification (SSI) method and the poly-reference least square complex frequency domain (pLSCF or PolyMAX) method, both of which came up with similar results. It was shown that the proposed excitation technique combined successfully with OMA methods to extract dynamic modal parameters of the machine tool structure.     

Method for the Optimization of Kinematic and Dynamic Properties of Parallel Kinematic Machines

The following paper introduces an approach, which allows the consideration of the kinematic as well as the dynamic properties of parallel kinematic machines. Based on the results of a preceding kinematic optimization, a FEM-model with arbitrary input parameters is designed. The full kinematic functionality of struts and joints used is ensured. By coupling the FEM-model to the GNU Octave numerical program system, a variety of movements including machining forces can be simulated. A Broyden-Fletcher-Goldfarb-Shanno optimization algorithm, using GNU Octave, was written and coupled to the FEM-system. Now, this algorithm is able to influence the model's arbitrary input parameters during the optimization process. Thus, the model is optimized automatically for a certain machining process and/or dynamic behavior. This procedure is demonstrated using the example of a delta robot structure originally designed by Raymond Clavel [7].