Optimal design of the dynamic performance of the ultra-precision fly cutting machine tool

Ding, Yu; Rui, Xiaoting; Chang, Yu; Lu, Hanjing; Chen, Yiheng; Ding, Jianguo; Shehzad, Adeel; Chen, Gangli; Gu, Junjie

doi:10.1007/s00170-022-10502-x

Cited by 6 publications

(6 citation statements)

References 29 publications

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“…Chen and Zhao first developed a theoretical model to extract relative tool‐workpiece vibration from the machined surface and used this model to predict the surface roughness in SPDT. Recently, some researchers have investigated the dynamic modeling of UPFC and its impact on surface roughness generation, specifically taking tool‐tip vibration into account 11,16–20 . Ding et al 16 developed a dynamic model of the UPFC machine tool using the transfer matrix method for multibody system (MSTMM) 21 and simulated the tool‐tip vibration.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the principles of mechanical system dynamics, the authors modeled the UPFC and estimated the tool‐tip vibration. Ding et al 18 used the FEM to develop a dynamic model of the cutter head, facilitating an accurate estimation of the tool‐tip displacement. Furthermore, they achieved a significant reduction of 16.97% in tool‐tip displacement through the implementation of an optimization scheme for the fly‐cutting head.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, some researchers have investigated the dynamic modeling of UPFC and its impact on surface roughness generation, specifically taking tool-tip vibration into account. 11,[16][17][18][19][20] Ding et al 16 developed a dynamic model of the UPFC machine tool using the transfer matrix method for multibody system (MSTMM) 21 and simulated the tool-tip vibration. Although their method was computationally efficient, the model did not consider the effect of material-induced vibration.…”

mentioning

confidence: 99%

“…Based on the principles of mechanical system dynamics, the authors modeled the UPFC and estimated the tool-tip vibration. Ding et al 18 used the FEM to develop a dynamic model of the cutter head, facilitating an accurate estimation of the tool-tip displacement.…”

mentioning

confidence: 99%

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Tool‐tip vibration prediction based on a novel convolutional enhanced transformer

Shehzad,

Rui,

Ding

et al. 2024

Int Journal of Mech Sys Dyn

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Superior surface finish remains a fundamental criterion in precision machining operations, and tool‐tip vibration is an important factor that significantly influences the quality of the machined surface. Physics‐based models heavily rely on assumptions for model simplification when applied to complex high‐end systems. However, these assumptions may come at the cost of compromising the model's accuracy. In contrast, data‐driven techniques have emerged as an attractive alternative for tasks such as prediction and complex system analysis. To exploit the advantages of data‐driven models, this study introduces a novel convolutional enhanced transformer model for tool‐tip vibration prediction, referred to as CeT‐TV. The effectiveness of this model is demonstrated through its successful application in ultra‐precision fly‐cutting (UPFC) operations. Two distinct variants of the model, namely, guided and nonguided CeT‐TV, were developed and rigorously tested on a data set custom‐tailored for UPFC applications. The results reveal that the guided CeT‐TV model exhibits outstanding performance, characterized by the lowest mean absolute error and root mean square error values. Additionally, the model demonstrates excellent agreement between the predicted values and the actual measurements, thus underlining its efficiency and potential for predicting the tool‐tip vibration in the context of UPFC.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Tool‐tip vibration prediction based on a novel convolutional enhanced transformer

Shehzad,

Rui,

Ding

et al. 2024

Int Journal of Mech Sys Dyn

Self Cite

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“…the negative impact of multi-source vibration on machining accuracy [2][3][4]. In fact, as a vital factor for the machining process, vibration decides whether the product can be machining with high accuracy [5,6].…”

Section: Introductionmentioning

confidence: 99%

A smart structural optimization method of magnetorheological damper for ultra-precision machine tool

Wang,

Shen,

et al. 2024

Smart Mater. Struct.

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To address the problem of multi-source vibration in ultra-precision machine tools, a vibration reduction stand was designed by replacing passive damping components with magnetorheological dampers (MRDs). In this work, the structural parameters of MRDs were optimized using an improved pelican optimization algorithm (IPOA) to realize the maximum capability in reducing vibration. Firstly, the working principle of MRDs was explained, and the mathematical models of MRDs were established. Then, an IPOA based on singer chaotic mapping, nonlinear inertia weight factor, and Cauchy mutation strategy was proposed to enhance the global search capability and convergence efficiency of the algorithm. Subsequently, the IPOA was applied to optimize key structural parameters of MRDs, including output damping force, controllable damping range, response time, and power consumption. Finally, COMSOL Multiphysics software was used to verify the effectiveness of the proposed algorithm by comparing the magnetic induction intensity distribution of MRDs before and after optimization, as well as the variation of the four performance indexes under the different applied currents. After being optimized using the proposed IPOA, the MRDs can deliver a larger maximum damping force and a wider damping controllable range, with less power consumption and quick response, which could meet the requirement for vibration suppression of ultra-precision machine tools.

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Effect of aerostatic spindle dynamic characteristics on the medium frequency waviness error of silicon wafer surface

Li,

Zhu,

Kang

et al. 2023

Int J Adv Manuf Technol

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Optimal design of the dynamic performance of the ultra-precision fly cutting machine tool

Cited by 6 publications

References 29 publications

Tool‐tip vibration prediction based on a novel convolutional enhanced transformer

Tool‐tip vibration prediction based on a novel convolutional enhanced transformer

A smart structural optimization method of magnetorheological damper for ultra-precision machine tool

Effect of aerostatic spindle dynamic characteristics on the medium frequency waviness error of silicon wafer surface

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