An improved thermal model for characteristics analysis of multi-link ultra-precision press system

Zheng, Enlai; Xie, Shilu; Jin, Zhang; Zhu, Yue; Zhao, Xiao; Lin, Xiangze; Kang, Min

doi:10.1007/s12206-017-1230-x

Cited by 7 publications

(4 citation statements)

References 31 publications

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“…Research conducted by Bryan indicates that thermal error can contribute to 40% − 70% of the total error in precision machining processes (Bryan 1990). In the case of high-end machine tools, this percentage can exceed 70% (Zheng et al 2018). Consequently, reducing thermal error has become a pressing issue to address in the precision machining of machine tools.…”

Section: Introductionmentioning

confidence: 99%

Exogenous input autoregressive model optimization based on mixed variables for offline prediction CNC Swiss lathes thermal errors

Wu,

Kong,

Wang

et al. 2023

Preprint

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Accurate prediction models of thermal errors are very useful for improving the machining accuracy of machine tools; it is also the core of thermal error compensation technology. Often, it is preferable to predict thermal deformation using the exogenous input autoregressive model, as opposed to computational inaccuracy and non-robustness existing in the static model. However, the autoregressive model needs to measure the thermal error online, which can be intrusive to the production process and reduce production efficiency. Previously, applying models to solving the engineering problem of machine thermal errors requires balancing accuracy and productivity. To simultaneously ensure prediction accuracy, robustness and productivity, this paper presents a new exogenous input autoregressive modeling approach based on mixed variables (MV-ARX) in CNC Swiss lathes. In addition, offline prediction is achieved by replacing online measurements with estimates of thermal errors. The effects of factors on thermal error, such as ambient temperature and spindle speed, are analyzed through thermal characteristic experiments. The K-means clustering method was used to select the thermal critical point, and the exogenous input autoregressive prediction model was optimized by combining the selected temperature variables with the spindle speed to improve the accuracy and robustness of offline prediction. The effectiveness of the proposed model is verified by comparing it with conventional models based on temperature-variable autoregression (TV-ARX) and multiple linear regression (MLR).

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Section: Introductionmentioning

confidence: 99%

Exogenous input autoregressive model optimization based on mixed variables for offline prediction CNC Swiss lathes thermal errors

Wu,

Kong,

Wang

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Research conducted by Bryan [1] indicates that thermal error can contribute to 40% -70% of the total error in precision machining processes. In the case of high-end machine tools, this percentage can exceed 70% [2]. Consequently, reducing thermal error has become a pressing issue to address in the precision machining of machine tools.…”

Section: Introductionmentioning

confidence: 99%

Exogenous input autoregressive model based on mixed variables for offline prediction thermal errors of CNC Swiss lathes

Wu,

Kong,

Wang

et al. 2023

Int J Adv Manuf Technol

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Accurate prediction models of thermal errors are very useful for improving the machining accuracy of machine tools; it is also the core of thermal error compensation technology. Often, it is preferable to predict thermal deformation using a dynamic model, as opposed to computational inaccuracy and non-robustness existing in the static model. Autoregressive models are one of the most commonly used dynamic models. However, the autoregressive model needs to measure the thermal error online, which can be intrusive to the production process and reduce production efficiency. This paper presents a new exogenous input autoregressive modeling approach based on mixed variables (MV-ARX) in CNC Swiss lathes. In addition, offline prediction is achieved by replacing online measurements with estimates of thermal errors. The effects of factors on thermal error, such as ambient temperature and spindle speed, are analyzed through thermal characteristic experiments. The K-means clustering method was used to select the thermal critical point, and the exogenous input autoregressive prediction model was optimized by combining the selected temperature variables with the spindle speed to improve the accuracy and robustness of offline prediction. Compared with the model based on temperature-variable autoregression (TV-ARX) and multivariate linear regression (MLR), the proposed model shows better prediction performance.The offline prediction of thermal errors also showed good performance under non-training conditions, with an offline prediction accuracy of up to 83.52%. The modeling method proposed in this work may pave the way for improving the prediction of other errors with similar nonlinear hysteresis dynamical systems.

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“…When thermal contact resistance and heat generation variation with respect to bearing temperature rise are considered, Zheng et al [37] developed a FE thermal model of the high-speed precision presses and predicted its temperature rise and thermal-induced error. Furthermore, considering the effect of linkage flexibility and lubricating oil on heat generation of bearings, Zheng et al [38,39] studied the temperature field and thermal deformation variation law of the crankshaft-rotor-bearing system for MHSPP through FEM.…”

Section: Introductionmentioning

confidence: 99%

Multi-body Dynamic Modelling and Error Analysis of Planar Flexible Multilink Mechanism Considering Clearance and Thermal-mechanical Coupling Effect of the Crankshaft-bearing Structure

Long¹,

Zhao²,

Jiang³

et al. 2021

Preprint

Self Cite

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In order to study the dynamic position accuracy of bottom dead point (BDP) for multilink high-speed precision presses (MHSPPs), it’s essential to develop a dynamic model of planar multilink mechanism with clearance and spindle-bearing structure. Traditional models always neglect the effect of thermal characteristics of spindle-bearing structure, which reduces the prediction accuracy of dynamic model for multilink transmission mechanisms. To overcome the shortcomings of the previous models, a thermal network model (TNM) of the crankshaft-bearing system is established firstly considering the effects of thermal contact resistance and variable stiffness of bearing concerning the temperature rise. Then, dynamic model of the crankshaft-bearing system is built through the finite element method, which includes rigid disk, Timoshenko beam and quasi-statics model of ACBB. On this basis, an improved dynamic model of planar flexible multilink mechanism with clearance considering the thermal-mechanical coupling effect of the crankshaft-bearing structure is developed and the corresponding dynamic error dimension chain between slider and crankshaft is constructed in this work. Compared to the simulation from traditional models, the simulated slider’s BPD position error from the improved model agrees better with experimental data, which verifies the correctness of the proposed model. It’s demonstrated that the punching force and thermally induced variable stiffness of bearing lead to a significant increase of slider’s BDP position error, which reduces the machining precision of MHSPP. Furthermore, the influence of crankshaft speed, contact angle of bearing and clearance size on the slider’s BDP position error is also investigated.

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An improved thermal model for characteristics analysis of multi-link ultra-precision press system

Cited by 7 publications

References 31 publications

Exogenous input autoregressive model optimization based on mixed variables for offline prediction CNC Swiss lathes thermal errors

Exogenous input autoregressive model optimization based on mixed variables for offline prediction CNC Swiss lathes thermal errors

Exogenous input autoregressive model based on mixed variables for offline prediction thermal errors of CNC Swiss lathes

Multi-body Dynamic Modelling and Error Analysis of Planar Flexible Multilink Mechanism Considering Clearance and Thermal-mechanical Coupling Effect of the Crankshaft-bearing Structure

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