A review on vibration analysis and control of machine tool feed drive systems

Yang, Haojin; Wang, Zihao; Zhang, Tao; Du, Fuxin

doi:10.1007/s00170-020-05041-2

Cited by 57 publications

(29 citation statements)

References 108 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a moving part of general equipment, a linear worktable's accuracy has an important influence on the working accuracy of the equipment. e factors that affect the accuracy of motion of the feeding worktable mainly include static errors [1] such as geometric errors, thermal errors of the mechanical parts, and dynamic errors [2] such as deformation and vibration during operation of the worktable, respectively. Among them, the research on the static error has been relatively complete [3][4][5][6][7], while the impact of the dynamic error factors on the accuracy of equipment becomes an issue.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Creeping Phenomenon of Linear Feed System Based on the Rigid‐Flexible Coupling Model

Liang

Hao

Ran

et al. 2021

Shock and Vibration

View full text Add to dashboard Cite

A mathematical model of the creeping phenomenon based on the mechanical model of the linear feed system was established. The dynamic characteristic parameters of each fixed joint were obtained by Yoshimura’s integral. Using the method, only the dynamic characteristic parameters of the joint surface per unit area with simple structure need to be studied, and then, the dynamic characteristic parameters of the whole joint surface can be obtained by integration. Based on the principle of the half-power bandwidth method and the frequency response function identification, the dynamic parameters of each moving joint were solved by the method of experimental modal analysis. Through the parameters of the fixed and moving joints, a rigid body model of the feed system and a flexible body model including the power transmission parts (ball screw pair) and the motion guide parts (guide slide pair and rolling bearing) were, respectively, established. And then, a rigid-flexible coupling dynamic model of the feed system was obtained through the constraint relationships between joints. The influence of both the external load and the feed rate on the fluctuation of motion speed of the system was analyzed from this model. The difference between the experimental results and the simulation results on a feed system platform is not greater than 10%, which verifies the creeping phenomenon. This conclusion can provide a basis for the optimization of the dynamic performance of the ball screw linear-feeding workbench.

show abstract

Section: Introductionmentioning

confidence: 99%

Analysis of the Creeping Phenomenon of Linear Feed System Based on the Rigid‐Flexible Coupling Model

Liang

Hao

Ran

et al. 2021

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…Regarding the joint unit, various studies have researched the properties of linear guideways, ball screws, and bearings [23][24][25][26][27][28][29][30]. Focusing on support stiffness, the present study revealed the dynamic characteristics of the machine structure by conducting impact testing at each stage of the machine's assembly process.…”

Section: Experimental Methods and Proceduresmentioning

confidence: 96%

A novel identification technique of machine tool support stiffness under the variance of structural weight

Zhuang

Liu

2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

The preload-dependent stiffness of machine tool support was investigated in this study. A novel identification method of support stiffness has been proposed through the experimental modal analysis and finite element method. The support stiffness was identified with different machine weight during the assembling process of a machining center. Specifically, the structure weight increase of a machine tool in the assembly process causes its center of gravity to shift. Accordingly, the variance of support reaction affects the support stiffness. To explore the variance of support stiffness, the researchers of this study collaborated with a machine tool manufacturer. Impact testing was performed on each assembly stage. Additionally, finite element analysis was used to establish equations between the reaction force versus stiffness of supports under the structural weight variance. The obtained equations were used to predict the natural frequency and vibration mode of structures in various assembly stages. The maximum error between the experimental and simulated natural frequencies was 7.1%, and the minimum modal assurance criterion was 0.77. Finally, a modal analysis model that updates support stiffness automatically, which could be adopted by machine builders to develop new machine tool, is proposed.

show abstract

“…Finally, the correctness of the mechanical design was verified [5]. Yang et al (2020) believed that with the development of modern manufacturing industry, the requirements for the performance of CNC machine tools are higher and higher; for high precision CNC machine tools, vibration in high-speed machining is an important factor affecting machining accuracy; as an important part of CNC machine tool, the dynamic characteristics of feed driving system have a great influence on the machining performance. Ball screw drive system is widely used in most CNC machines.…”

Section: Introductionmentioning

confidence: 97%

Control Parameter Optimization-Based Machining Control Technology of State-of-the Art Computer Numerical Control Machine Tools

2021

IJOMAM

View full text Add to dashboard Cite

In order to improve the accuracy, reliability and efficiency of computer numerical control (CNC) machine tools, first, according to the working principle of servo motor and related physical relations, the mathematical model of servo system is established. Moreover, the mathematical model is used to establish the three-closed loop simulation structure of servo. Then, according to the simulation structure, a parameter optimization algorithm of CNC machine tool servo system based on improved particle swarm optimization (PSO) algorithm is proposed. Compared with the previous PSO algorithm, the PSO algorithm used has two improvements. First, it introduces the nonlinear dynamic inertia weight coefficient, and constructs the functional relationship between accelerated factor and inertia weight. Second, it introduces the extreme perturbation operator to increase the search range of particles. Moreover, the improved PSO algorithm is used to optimize the scale factor parameters in the regulator. The experimental results show that the dynamic performance of CNC machine tool servo system has been improved to a certain extent. Compared with the Proportion Integration Differentiation (PID) parameters without tuning, the overshoot of the system is reduced and the robustness is improved. In addition, the tuning PID parameters are compared with those of crowd search algorithm (SOA), PSO and genetic algorithm (GA). The results show that the adjustment time to the stable error of the CNC machine tool servo system optimized by GA algorithm is longer than other algorithms, and the oscillation of the transition time is severer. The PID parameters of CNC machine tool servo system optimized by improved PSO algorithm are obviously better than those optimized by other algorithms. The system using this parameter has a short adjustment time and an overshoot of 0. Therefore, the performance of the improved PSO algorithm is better than SOA, PSO and GA algorithm. The proposed algorithm provides a new idea for intelligent algorithm to solve the control parameter optimization problem of CNC machine tools.

show abstract

A review on vibration analysis and control of machine tool feed drive systems

Cited by 57 publications

References 108 publications

Analysis of the Creeping Phenomenon of Linear Feed System Based on the Rigid‐Flexible Coupling Model

Analysis of the Creeping Phenomenon of Linear Feed System Based on the Rigid‐Flexible Coupling Model

A novel identification technique of machine tool support stiffness under the variance of structural weight

Control Parameter Optimization-Based Machining Control Technology of State-of-the Art Computer Numerical Control Machine Tools

Contact Info

Product

Resources

About