A Novel Updated Full-Discretization Method for Prediction of Milling Stability

Li, Yunfei; Zhang, Dinghua; Zhao, Bo; Wang, Geng; Pang, Xiaoyan

doi:10.3390/mi13020160

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…Then, five slotting tests were carried out with a spindle speed of 1000 r/min and an axial depth of cut of 0.5 mm, while the feed rates were 40 mm/min, 80 mm/min, 120 mm/min, 160 mm/min, and 200 mm/min. Then, the milling force coefficient and the average milling force were obtained [ 36 , 39 ].

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Section: Experimental Validation and Discussionmentioning

confidence: 99%

Output-Only Time-Varying Modal Parameter Identification Method Based on the TARMAX Model for the Milling of a Thin-Walled Workpiece

Yan

et al. 2022

Micromachines

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The process parameters chosen for high-performance machining in the milling of a thin-walled workpiece are determined by a stability prediction model, which needs accurate modal parameters of the machining system. However, the in-process modal parameters are different from the offline modal parameters and are difficult to precisely obtain due to material removal. To address this problem, an accurate time-dependent autoregressive moving average with an exogenous input (TARMAX) method is proposed for the identification of the modal parameters in the milling of a thin-walled workpiece. In this process, a TARMAX model considering external force excitation is constructed to characterize the actual condition in the milling of a thin-walled workpiece. Then, recursive method and sliding window recursive method are used to identify TARMAX model parameters under time-varying cutting conditions. Subsequently, a three-degree of freedom (3-DOF) time-varying structure numerical model under theoretical milling forces and white-noise excitation is established, and the computational results show that the predicted natural frequencies using the proposed method are in close agreement with the simulated values. Finally, several experiments are designed and carried out to validate the effectiveness of the proposed method. The experimental results show that the predicted accuracy of the proposed method using actual cutting forces is 95.68%. Good agreement has been drawn in the numerical simulation and machining experiments. Our further research objectives will focus on the prediction of the damping ratios, modal stiffness, and modal mass.

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…”

Section: Experimental Validation and Discussionmentioning

confidence: 99%

Output-Only Time-Varying Modal Parameter Identification Method Based on the TARMAX Model for the Milling of a Thin-Walled Workpiece

Yan

et al. 2022

Micromachines

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“…The adaptive variable-step numerical integration method takes into account the effect of the helix angle and improves the discretization accuracy of the cutting period, and thus improves the calculation accuracy of the milling stability limit. Ma et al [ 30 ] presented an updated FDM for milling stability prediction based on cubic spline interpolation. Zheng et al [ 31 ] proposed a numerical method based on the composited Newton–Cotes formula to predict milling stability.…”

Section: Introductionmentioning

confidence: 99%

Stability Analysis in Milling Based on the Localized Differential Quadrature Method

Mei,

He,

et al. 2023

Micromachines

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Chatter stability analysis is an effective way to optimize the cutting parameters and achieve chatter-free machining. This paper proposes a milling chatter stability analysis method based on the localized differential quadrature method (LDQM), which has the advantages of simple principle, easy application, and high computational efficiency. The milling process, considering the regeneration effect, is modeled using linear periodic delay differential equations (DDE), then the state transition matrix during the adjacent cutting period is constructed based on the LDQM, and finally, the stability of the milling process is obtained based on the Floquet theory. The accuracy and computation efficiency of the proposed method are verified through two benchmark milling models. The simulation results demonstrate that the proposed method in this paper can accurately and quickly obtain the chatter stability lobe diagram (SLD) of the milling process, which will provide guidance for optimizing the process parameters.

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“…Regenerative chatter arising from a self-excitation chatter vibration may be unavoidable in milling processes, which will reduce machining quality and efficiency and accelerate tool wear [ 1 , 2 ]. Researchers have attempted to avoid regenerative chatter using prediction [ 3 , 4 ], identification [ 5 , 6 , 7 ], and suppression [ 8 , 9 , 10 ] methods.…”

Section: Introductionmentioning

confidence: 99%

Milling Stability Prediction: A New Approach Based on a Composited Newton–Cotes Formula

et al. 2023

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Based on a composited Newton–Cotes formula, this paper proposes a numerical method to predict milling stability considering regenerative chatter and focusing on rate and prediction accuracy. First, the dynamic model of milling motion is expressed as state-space equations considering regenerative chatter, with the tooth passing period divided into a set of time intervals. Second, a composited Newton–Cotes formula is introduced to calculate the transition function map for each time interval. Third, the state transition matrix is constructed based on the above-mentioned transition function, and the prediction stability boundary is determined by the Floquet theory. Finally, simulation analysis and experimental verification are conducted to verify the effectiveness of the proposed method. The simulation results demonstrate that, for the milling model with a single degree of freedom (DOF), the convergence rate and prediction accuracy of the proposed method are higher than those of the comparison method. The experimental results demonstrate that, for the milling model with two DOFs, the machining parameters below the prediction stability boundary can avoid the chatter as much as possible, ensuring the machined surface quality.

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A Novel Updated Full-Discretization Method for Prediction of Milling Stability

Cited by 8 publications

References 28 publications

Output-Only Time-Varying Modal Parameter Identification Method Based on the TARMAX Model for the Milling of a Thin-Walled Workpiece

Output-Only Time-Varying Modal Parameter Identification Method Based on the TARMAX Model for the Milling of a Thin-Walled Workpiece

Stability Analysis in Milling Based on the Localized Differential Quadrature Method

Milling Stability Prediction: A New Approach Based on a Composited Newton–Cotes Formula

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