Tool point frequency response function prediction using RCSA based on Timoshenko beam model

Qi, Bin; Sun, Yuwen; Li, Zhongyun

doi:10.1007/s00170-017-0236-y

Cited by 14 publications

(2 citation statements)

References 27 publications

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“…Another potential source of uncertainty in the predicted FRF at the tool's tip is the accuracy of finite element analysis (FEA) based models representing the tools. In [14] (Qi et al) the authors compared Timoshenko and Euler-Bernoulli beam representations of tool body in tool-tip FRF prediction using RCSA and verified the method on simplified slender cylinders representing tool geometries differing in lengths. Albertelli et al [15] presents improved RCSA method where rotation/moment receptance is estimated via 9 dynamic compliance measurements on spindle-holder assembly and spindle-holder-tool assembly and "new tool" receptances are calculated via 3D FEA.…”

Section: Introductionmentioning

confidence: 99%

Single artifact inverse RCSA with improved cross compliance identification

Sulitka,

Falta,

Kohut

2024

Preprint

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The Frequency Response Function (FRF) at the tool-tip is important input for machining dynamics prediction, but its measurement is a time-intensive process. The receptance coupling technique offers a faster alternative, suitable for industrial applications where there is experimentally identified receptance matrix at machine-tool holder interface containing enough degrees of freedom to allow connection with various compliant tools modelled using finite element analysis (FEA). The presented approach to the technique further develops simplification of the inverse RCSA by using a single artifact proposed by Montevecchi, presenting simpler and more general mathematical formulation of the receptance matrix identification. The study also looked into how simplifying tool models affects their accuracy and performance in FEA, aiming to find a good balance between detail and efficiency. To prove the proposed technique, thorough tests on two dynamically different machine tools were conducted with various tool geometries.

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Section: Introductionmentioning

confidence: 99%

Single artifact inverse RCSA with improved cross compliance identification

Sulitka,

Falta,

Kohut

2024

Preprint

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“…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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A new method using double distributed joint interface model for three-dimensional dynamics prediction of spindle-holder-tool system

Yang

Wan

et al. 2017

Int J Adv Manuf Technol

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Tool point frequency response function prediction using RCSA based on Timoshenko beam model

Cited by 14 publications

References 27 publications

Single artifact inverse RCSA with improved cross compliance identification

Single artifact inverse RCSA with improved cross compliance identification

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

A new method using double distributed joint interface model for three-dimensional dynamics prediction of spindle-holder-tool system

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