A new modeling method for thermal errors of motorized spindle based on the variation characteristics of spindle temperat
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ORIGINAL ARTICLE
A new modeling method for thermal errors of motorized spindle based on the variation characteristics of spindle temperature field Zongzhuo Yan 1,2
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Tao Tao 1,2,3
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Ruisheng Hou 1,3,4 & Hongyang Du 1,3 & Xuesong Mei 1,2,3
Received: 3 January 2020 / Accepted: 8 July 2020 / Published online: 18 August 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Motorized spindle is a component with complex thermal properties. Its thermal boundary conditions change with operating conditions, and thus, the variations of spindle temperature field under different conditions are not exactly the same. Models with fixed structures and fixed coefficients have difficulty in predicting the spindle thermal error with high accuracy and stability. To solve this problem, study of the variation rules of the spindle temperature field is conducted in this paper. The variation process is divided into two stages: the non-uniform variation stage and the uniform variation stage. The variation characteristics are concluded into two parts: the overall variation tendency and the variation of temperature distribution from the inside to outside of the spindle. These conclusions provide a new perspective for temperature variable selection and coefficients adjustment. Based on the variation characteristics of the spindle temperature field, a new modeling method for spindle thermal errors is proposed. The basic temperature, the difference between temperature near the internal heat source and the basic temperature, and the ambient temperature are applied as input variables. The coefficient of the second input variable is set to adjust adaptively according to the spindle status. This method puts more emphasis on the variation rules of the spindle temperature field and can significantly increase the accuracy and the robustness of the prediction model. The model coefficients are optimized by PSO (particle swarm optimization). According to the experimental verification, the variation ranges of residual errors are reduced by at least 62% when predicting the thermal error in X-direction with the proposed model. Keywords Motorized spindle . Temperature field variations . Thermal error modeling . Model adaptation
1 Introduction Motorized spindles are widely used in modern precision machining due to their high accuracy, high speed, and low noise. But the thermal errors caused by the remarkable temperature rise of the motorized spindle seriously decrease the machining
* Tao Tao [email protected] 1
State Key Laboratory for Manufacturing System Engineering, No. 28, Xianning West Road, Xi’an 710049, People’s Republic of China
2
School of Mechanical Engineering, Xi’an Jiaotong University, No. 28, Xianning West Road, Xi’an 710049, People’s Republic of China
3
Shaanxi Key Laboratory of Intelligent Robots, No. 28, Xianning West Road, Xi’an 710049, People’s Republic of China
4
School of Machinery and Equipment Engineering, Hebei University of Engineering, Taiji Road 19, Handan 056038, People’s Republic of China
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