Analysis of Dynamic Characteristics for Machine Tools Based on Dynamic Stiffness Sensitivity

Li, Chunhui; Song, Zhiqiang; Huang, Xianghua; Zhao, Hui; Jiang, Xuchu; Mao, Xinyong

doi:10.3390/pr9122260

Cited by 6 publications

(4 citation statements)

References 25 publications

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“…The extracted features are employed to investigate the information pertaining to the future time. The vibration data of a machine tool are used to illustrate the dynamic characteristics of the machine [32]. The amplitude of vibrations in different states exhibit a varying temporal profile (Figure 13).…”

Section: Data Acquisitionmentioning

confidence: 99%

A Fault Prediction Method for CNC Machine Tools Based on SE-ResNet-Transformer

Wu,

He,

Wang

et al. 2024

Machines

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Aiming at the problem that predicted data do not reflect the operating status of computer numerical control (CNC) machine tools, this article proposes a new combined model based on SE-ResNet and Transformer for CNC machine tool failure prediction. Firstly, the Transformer model is utilised to build a non-linear temporal feature mapping using the attention mechanism in multidimensional data. Secondly, the predicted data are transformed into 2D features by the SE-ResNet model, which is adept at processing 2D data, and the spatial feature relationships between predicted data are captured, thus enhancing the state recognition capability. Through experiments, data involving the CNC machine tools in different states are collected to build a dataset, and the method is validated. The SE-ResNet-Transformer model can accurately predict the state of CNC machine tools with a recognition rate of 98.56%. Results prove the effectiveness of the proposed method in CNC machine tool failure prediction. The SE-ResNet-Transformer model is a promising approach for CNC machine tool failure prediction. The method shows great potential in improving the accuracy and efficiency of CNC machine tool failure prediction. Feasible methods are provided for precise control of the state of CNC machine tools.

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Section: Data Acquisitionmentioning

confidence: 99%

A Fault Prediction Method for CNC Machine Tools Based on SE-ResNet-Transformer

Wu,

He,

Wang

et al. 2024

Machines

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show abstract

“…When subjected to complicated external dynamic loads, joint component substructures are prone to micro-vibration with multi-directional degrees of freedom (DOFs). The joints will be able to show off the crucial characteristic of flexible connections by storing and dissipating energy and demonstrating elasticity and damping [57][58][59]. Statistics indicated that joint factors like damping and stiffness account for 30% to 50% of stiffness and 90% of the CNCMT's dynamic performance damping.…”

Section: Major Identification Elementmentioning

confidence: 99%

Analysis of Dual-Driven Feed System Vibration Characteristics Based on Computer Numerical Control Machine Tools: A Systematic Review

Chantal,

Lu,

Liu

et al. 2023

Symmetry

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Vibration in state-of-the-art machining impacts accuracy by diminishing the machine’s dynamic precision and the workpiece surface quality. The dependability of the cutters and productivity becomes a severe problem for optimizing the computer numerical control machine tools’ (CNCMT) efficiency. Therefore, investigating the twin ball screw drive system vibration properties as well as its corresponding control measures is vital. This paper thoroughly reviews the recent works on methods of analyzing and controlling vibration for dual-driven feed systems (DDFS). The research on vibration control technologies, parameter identification, and system modeling are identified and summarized; the merits and drawbacks of various methods are discussed for comparative purposes. Furthermore, the asymmetrical relation between DDFS and single-driven feed systems are thoroughly discussed based on their dynamic properties. Finally, based on existing studies, related research prospects are described systematically, and these research directions are sure to markedly contribute to developing methods for dampening vibrations on DDFS of CNCMT.

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“…Hence, it was considered to be a sensitive part of the holistic VMC to enhance the dynamics through stiffness improvement and mass reduction. 33 Further, limited results of investigations have been reported for the design and analysis of spindle head built with alternate materials. In the present work, the CI spindle head of the VMC depicted in Figure 1 is replaced with steel-reinforced EG with the objective of improving the dynamic performance of the spindle head which in turn improves the overall dynamics of VMC.…”

Section: Introductionmentioning

confidence: 99%

The influence of steel reinforcements on static rigidity of epoxy granite spindle head for dynamic performance enhancement of machining center: Experiments and finite element simulation

Dhanabal,

Thyla,

Kalayarasan

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part L:

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Machine tool structures are subjected to continuous distortions and unwanted vibrations during machining. The structures should have excellent static and dynamic properties to minimize the adverse effects due to vibration. Cast iron is generally used as a structural material for machine tools owing to its higher structural rigidity and moderate damping properties. The lack of desired dynamic properties results in poor surface finish of the machined components. Epoxy granite is a resin mineral-based composite found to provide superior damping ability but it has lesser material stiffness. Steel reinforcements are more appropriate to enhance the static rigidity of epoxy granite structures. The cast iron spindle head of the vertical machining center is considered for the present study. Static structural analysis has been performed by finite element analysis and the results are considered as a benchmark for the design of epoxy granite spindle head. Multiple design configurations of steel reinforcements are evolved through topology optimization to achieve improved stiffness with a higher damping ratio. A model which exhibited higher stiffness with minimum steel has been proposed for fabrication. A 1:2 scaled model of the proposed configuration has been fabricated using epoxy granite. Experimental modal analysis and numerical static analyses have been carried out and the results are compared to those of cast iron spindle head. A significant reduction in mass and deformation of the epoxy granite spindle head by 22% and 57%, respectively, was observed compared to that of cast iron spindle head.

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Analysis of Dynamic Characteristics for Machine Tools Based on Dynamic Stiffness Sensitivity

Cited by 6 publications

References 25 publications

A Fault Prediction Method for CNC Machine Tools Based on SE-ResNet-Transformer

A Fault Prediction Method for CNC Machine Tools Based on SE-ResNet-Transformer

Analysis of Dual-Driven Feed System Vibration Characteristics Based on Computer Numerical Control Machine Tools: A Systematic Review

The influence of steel reinforcements on static rigidity of epoxy granite spindle head for dynamic performance enhancement of machining center: Experiments and finite element simulation

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