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Dynamic thermal behavior and thermal error prediction of spindle due to periodic jump motions in a large precision die-sinking EDM machine

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Abstract

Thermal error which has been widely studied in cutting machine tools, was ignored in the EDM machines in most cases, since there is usually no high-speed rotation for spindles. However, for large die-sinking EDM machines, due to heavy load of drive system and long processing cycle of large aeronautical parts, thermal error induced by jump motion has seriously impaired the machining accuracy and gradually been recognized. In this paper, the dynamic thermal behavior of spindle induced by periodic jump motions in large precision die-sinking EDM machine was studied for the first time. Noted that the Z-axis base and column show obvious temperature rise and the thermal error in Y direction is the largest, which is about 6.5 and 5 times compared with that in X and Z directions. Based on this, an efficient thermal error prediction model was presented. Thermal sensitive points were picked out through fuzzy clustering and correlation theory, taken as inputs of radial basis function (RBF) neural network to guarantee the accuracy. As a result, the prediction accuracy in X, Y and Z directions are 95.2 %, 92.5 % and 94.4 %, respectively. Finally, the effect of jump period on spindle thermal behavior was investigated, and suggestions for optimizing jump motion parameters were proposed to further improve the machining accuracy of large EDM machines.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (Grant No. 51775145, 61771156), Major Project of Applied Technology Research and Development Plan of Heilongjiang Province (Grant No. GA16A404) and Open Found of Key Laboratory of Microsystems and Microstructure Manufacturing Ministry of Education (HIT) (Grant No. 2016KM010).

Author information

Authors and Affiliations

  1. Key Laboratory of Micro-systems and Micro-structures Manufacturing of Ministry of Education, Harbin Institute of Technology, Harbin, 150001, China

    Zhaoxi Zhao, Jia Zhang, Yukui Wang & Zhenlong Wang

  2. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, 150001, China

    Zhaoxi Zhao, Jia Zhang, Yukui Wang & Zhenlong Wang

  3. Beijing Institute of Electromachining, Beijing, 100000, China

    Jianyong Liu

  4. College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China

    Chenghao Quan

Authors
  1. Zhaoxi Zhao
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  2. Jia Zhang
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  3. Yukui Wang
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  4. Zhenlong Wang
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  5. Jianyong Liu
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Corresponding author

Correspondence to Zhenlong Wang.

Additional information

Recommended by Associate Editor Wonkyun Lee

Zhaoxi Zhao is a Ph.D. student in the School of Mechatronics Engineering of Harbin Institute of Technology and a member in Key Laboratory of Microsystems and Microstructures Manufacturing of Ministry of Education at the same institute. Her research work is focused on the dynamic and thermal analysis of large precision die-sinking EDM machine tools.

Zhenlong Wang is a Professor and an Associate Dean in the School of Mechatronics Engineering of Harbin Institute of Technology. His research area is on non-traditional machining technology, micro-machining technology, electromechanical control process and intelligent processing. In recent years, he has completed more than 30 projects, including the key projects of the National Natural Science Foundation and the National 863 Program, the advance research projects of the General Equipment Department, the basic scientific research projects of the National Defense Science and Industry Commission, and 973 projects.

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Zhao, Z., Zhang, J., Wang, Y. et al. Dynamic thermal behavior and thermal error prediction of spindle due to periodic jump motions in a large precision die-sinking EDM machine. J Mech Sci Technol 33, 3397–3405 (2019). https://doi.org/10.1007/s12206-019-0635-0

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  • DOI: https://doi.org/10.1007/s12206-019-0635-0

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