Abstract:Flexible parts are widely used in the aeronautic and power industries which have high machining accuracy requirement. However, the flexible part is apt to vibrate in cutting processes due to its low structure stiffness and damping. Accurate approximation of cutting stability boundary of flexible part is difficult, because traditional stability analysis simplifies the complex dynamic system and some parameters still have large vibrations and can cause bad surface accuracy even when they are predicted to be loca… Show more
“…Combine Eqs. (9) and (23), and the state transition relationship on a tooth passing period interval can be formulated as follows: …”
Section: Approximation Of Second Ordermentioning
confidence: 99%
“…In the early days, the time domain methods [6][7][8] are used for the simulations of chatter vibration in the cutting process, and they are quite suitable for complex situations, such as in the case of thin-walled part milling [9] and variable pitch end milling [10]. To improve the computation accuracy and efficiency of stability, much effort has been devoted to acquire the stability lobe diagrams analytically or semi-analytically.…”
A numerical differentiation method is presented to predict the high speed milling stability of a two degrees of freedom (DOF) system based on the finite difference method and extrapolation method. The milling dynamics taking the regenerative effect into account are represented as linear periodic delayed differential equations (DDE) in the state space form. Then, each component of the first derivative of the state function versus time at the discretized sampling grids is approximated as a weighted linear sums of the state function values at its neighboring grid points, where the weight coefficients are calculated based on the extrapolation method. As such, the DDE on the forced vibration duration is approximately discretized as a series of algebraic equations. Thereafter, the Floquet transition matrix can be constructed on one tooth passing period by combining the analytical solution of the free vibration and the algebraic equations of the forced vibration. Finally, the milling stability is determined according to Floquet theory. The stability diagrams and convergence of critical eigenvalues in comparison with the benchmark algorithms (the semi-discretization method and numerical integration method) via experimentally verified examples are utilized to demonstrate the effectiveness and efficiency of the proposed method.
“…Combine Eqs. (9) and (23), and the state transition relationship on a tooth passing period interval can be formulated as follows: …”
Section: Approximation Of Second Ordermentioning
confidence: 99%
“…In the early days, the time domain methods [6][7][8] are used for the simulations of chatter vibration in the cutting process, and they are quite suitable for complex situations, such as in the case of thin-walled part milling [9] and variable pitch end milling [10]. To improve the computation accuracy and efficiency of stability, much effort has been devoted to acquire the stability lobe diagrams analytically or semi-analytically.…”
A numerical differentiation method is presented to predict the high speed milling stability of a two degrees of freedom (DOF) system based on the finite difference method and extrapolation method. The milling dynamics taking the regenerative effect into account are represented as linear periodic delayed differential equations (DDE) in the state space form. Then, each component of the first derivative of the state function versus time at the discretized sampling grids is approximated as a weighted linear sums of the state function values at its neighboring grid points, where the weight coefficients are calculated based on the extrapolation method. As such, the DDE on the forced vibration duration is approximately discretized as a series of algebraic equations. Thereafter, the Floquet transition matrix can be constructed on one tooth passing period by combining the analytical solution of the free vibration and the algebraic equations of the forced vibration. Finally, the milling stability is determined according to Floquet theory. The stability diagrams and convergence of critical eigenvalues in comparison with the benchmark algorithms (the semi-discretization method and numerical integration method) via experimentally verified examples are utilized to demonstrate the effectiveness and efficiency of the proposed method.
“…For instance, Schmitz's team proposed methods to predict the SLE in time and frequency domain, and pointed out that the SLE was dependent on the machining parameters [21], [22]. As the SLE determines the geometric accuracy of the workpiece, it should be discussed in the machining parameters optimization [23]. Zhang et al [24] had emphasized uncertain parameters in milling process and established a formulation for obtaining the robust minimum SLE and maximum spindle speed.…”
In machining parameters optimization of a chatter-free milling process, the inevitable surface location error (SLE) reflecting the machined workpiece dimension accuracy has been barely considered as one objective representing the machining quality, lowering the optimization accuracy. Therefore, this paper provides an approach to establish a multi-objective optimization model, where the material removal rate (MRR) represents the machining efficiency and the SLE predicted in time-domain represents the machining quality. The non-dominated sorting genetic algorithm (NSGA-II) method is used to solve the multi-objective model and provide pareto optimal solutions to first determine some ideal optimal solutions. Then the analytic hierarchy process (AHP) and grey target decision (GTD) methods are combined to select one most satisfactory optimal solution which has a well balance between the MRR and SLE. A multi-objective model was established and taken as a case study to maximize the MRR and minimize the SLE. Comparison study was performed on this multi-objective model and two other mono-objective models for obtaining the optimal MRR and SLE respectively, which was combined with the influences of machining parameters on SLE to show the necessity of conducting a multi-objective optimization. Milling tests were conducted based on the solved optimal machining parameters, and the well consistence between the measured and predicted SLEs shows that the proposed multi-objective optimization method can provide an effective approach to balance the machining efficiency and quality when there are conflicts between different objectives.
“…Thevenot et al [33] reported a three dimension lobes construction method and applied it to thin-walled structure milling. Zhang et al [34] proposed a synthetical stability analysis method for flexible part milling, in this method the regenerative dynamic excitation and steady periodical excitation are simultaneously considered.…”
With the rapid development of aerospace technology, Al7075 has been widely used for structural components. High-speed milling is one of the most effective ways to improve machining efficiency of Al7075. During the milling process, regenerative chatter which restricts the milling quality and productivity often occurs. With the aim of avoiding regenerative chatter, stability lobe diagram (SLD) is widely used to obtain chatter-free parameters. This work presents a stability prediction method by using shifted Chebyshev polynomials. The milling dynamics with consideration of the regenerative effect is described by time periodic delaydifferential equations (DDEs). The transition matrix of the milling system is constructed with the help of ChebyshevGauss-Lobatto (CGL) points. In order to demonstrate the accuracy of the proposed method, the rate of convergence of the proposed method is compared with that of the classical benchmark methods. On the other hand, in the process of thinwalled workpiece milling, the dynamic behavior of the workpiece depends on the tool position. To study the influence of the tool position dependent dynamics on the chatter stability of the thin-walled workpiece, a three-dimensional SLD is obtained. The verification experiments are conducted to verify the reliability of the proposed method. The results show that the experimental results are consistent with the predicted results.
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