High speed tooltip FRF predictions of arbitrary tool-holder combinations based on operational spindle identification

Postel, Martin; Özşahin, Orkun; Altintaş, Yusuf

doi:10.1016/j.ijmachtools.2018.03.004

Cited by 57 publications

(14 citation statements)

References 20 publications

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“…Effect. According to formulas (8) and (9) for raceway control theory of a spindlebearing system, the bearing correction coefficient is adjusted for the characteristics of a ceramic Si 3 N 4 bearing to establish a ceramic bearing model and a metal bearing model, respectively. e conditions of simulation are radial dynamic stiffness, gyroscopic moment, and inner and outer ring contact angles of the bearing calculated under the working conditions of a preload force of 300-500 N and speed of 3000-30000 rpm.…”

Section: Spindle-bearing Dynamic Stiffnessmentioning

confidence: 99%

See 1 more Smart Citation

Research on Vibration Characteristics of a Ceramic Spindle Based on the Reverse Magnetic Effect

Zhang

Wang

Shi

et al. 2019

Shock and Vibration

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The electromagnetic radial force about a ceramic spindle affects the spindle dynamic, which determines the quality of processing. Using a Timoshenko beam unit to build the dynamic model for the ceramic spindle, the dynamic characteristic of an angular contact ball bearing is analyzed using a nonlinear bearing model. The electromagnetic magnetization model was established based on Maxwell’s theory to calculate electromagnetic magnetic density and radial force. The influence about the reverse magnetic field characteristic of the ceramic rotating shaft and dynamic stiffness of the contact ball bearing on the dynamic phenomena of the spindle is analyzed, which is verified by experiments. The results show that the magnetic effect produced by the reverse magnetic of ceramic rotation shaft has a great influence on the electromagnetic radial force. Compared with the paramagnetic effect of the metal shaft, the dynamic characteristics of the spindle can be significantly improved. Considering the coupling relationship between the radial force of the magnetic field and the bearing contact force, dynamic stiffness, and other factors, the accuracy of the model simulation is highly consistent with the test results. In particular, the ceramic spindle model has been successful in predicting with high accuracy and is suitable for multiple extreme working conditions. The parameters, such as initial eccentricity of the rotor, bearing preload, and rotating speed, can be adjusted to restrain the vibration of spindle. The ceramic spindle model provides a theoretical basis for the dynamics development of a high-speed spindle.

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Section: Spindle-bearing Dynamic Stiffnessmentioning

confidence: 99%

“…e model can not perform the vibration accurately in some extreme cases. Some papers [8][9][10] proposed speed-dependent FRF (Frequency Response Function) spindle model. e coupled spindle model based on Timoshenko beam can be predicted.…”

Section: Introductionmentioning

confidence: 99%

Research on Vibration Characteristics of a Ceramic Spindle Based on the Reverse Magnetic Effect

Zhang

Wang

Shi

et al. 2019

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…The research on tool system dynamics [ 18 ] and machine tool performance [ 19 ] has received more attention. The performance of the machine tool is very important to the improvement of machining quality and efficiency [ 20 ]. The finite element method is used to establish a model close to the real machine tool structure, analyze its performance, and achieve the purpose of improving efficiency.…”

Section: Introductionmentioning

confidence: 99%

Cutting Force Transition Model Considering the Influence of Tool System by Using Standard Test Table

Chen

Zhang

Wang

2021

Sensors

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The cutting force prediction model usually uses the classical oblique transformation method, which introduces the orthogonal cutting parameters into the oblique milling edge shape, and combines the geometric parameters of the tool to convert the orthogonal cutting force into the actual cutting force, thereby predicting the cutting force. However, this cutting force prediction method ignores the impact of tool vibration in actual machining, resulting in a large difference between the prediction model and the actual measurement. This paper proposes a cutting force conversion model considering the influence of the tool system. The proposed model fully considers the impact of tool vibration on the cutting force. On the basis of the orthogonal model, superimposing the additional cutting force generated by tool vibration makes the predicted value of the model closer to the actual cutting force. The results of milling experiments show that the conversion model can obtain higher prediction accuracy. Moreover, compared with the original conversion model, the accuracy of the proposed model is significantly improved.

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“…Ji et al [10] proposed a new receptance coupling substructure analysis methodology to predict the tool tip dynamics solving the accuracy problem in the estimation of the rotational/moment receptance. Postel et al [11] presented a new approach for prediction of tooltip FRFs under operational conditions for arbitrary tool-holder combinations. Qi et al [12] presented tool point frequency response prediction based on Timoshenko beam model using receptance theory.…”

Section: Introductionmentioning

confidence: 99%

Dynamical Contact Parameter Identification of Spindle-Holder-Tool Assemblies Using Soft Computing Techniques

Čiča

Zeljković²,

Tešić³

2020

FU Mech Eng

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In industry, the capability to predict the tool point frequency response function (FRF) is an essential matter in order to ensure the stability of cutting processes. Fast and accurate identification of contact parameters in spindle-holder-tool assemblies is very important issue in machining dynamics analysis. This work is an attempt to illustrate the utility of soft computing techniques in identification and prediction contact parameters of spindle-holder-tool assemblies. In this paper, three soft computing techniques, namely, genetic algorithm (GA), simulated annealing (SA), and particle swarm optimization (PSO) were used for identification of contact dynamics in spindle-holder-tool assemblies. In order to verify the proposed identification approaches, numerical and experimental analysis of the spindle-holder-tool assembly was carried out and the results are presented. Finally, a model based on the adaptive neural fuzzy inference system (ANFIS) was used to predict the dynamical contact parameters at the holder-tool interface of a spindle-holder-tool assembly. Accuracy and performance of the ANFIS model has been found to be satisfactory while validated with experimental results.

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High speed tooltip FRF predictions of arbitrary tool-holder combinations based on operational spindle identification

Cited by 57 publications

References 20 publications

Research on Vibration Characteristics of a Ceramic Spindle Based on the Reverse Magnetic Effect

Research on Vibration Characteristics of a Ceramic Spindle Based on the Reverse Magnetic Effect

Cutting Force Transition Model Considering the Influence of Tool System by Using Standard Test Table

Dynamical Contact Parameter Identification of Spindle-Holder-Tool Assemblies Using Soft Computing Techniques

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