A Linear Regression Thermal Displacement Lathe Spindle Model

Chih-Jer Lin, Xiao-Yi Su, Chi-Hsien Hu, Bo-Lin Jian, Li-Wei Wu and Her-Terng Yau
Additional contact information
Chih-Jer Lin: Graduate Institute of automation Technology, National Taipei University of Technology, Taipei 10608, Taiwan
Xiao-Yi Su: Graduate Institute of automation Technology, National Taipei University of Technology, Taipei 10608, Taiwan
Chi-Hsien Hu: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Bo-Lin Jian: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Li-Wei Wu: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Her-Terng Yau: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan

Energies, 2020, vol. 13, issue 4, 1-14

Abstract: Thermal error is one of the main reasons for the loss of accuracy in lathe machining. In this study, a thermal deformation compensation model is presented that can reduce the influence of spindle thermal error on machining accuracy. The method used involves the collection of temperature data from the front and rear spindle bearings by means of embedded sensors in the bearing housings. Room temperature data were also collected as well as the thermal elongation of the main shaft. The data were used in a linear regression model to establish a robust model with strong predictive capability. Three methods were used: (1) Comsol was used for finite element analysis and the results were compared with actual measured temperatures. (2) This method involved the adjustment of the parameters of the linear regression model using the indicators of the coefficient of determination, root mean square error, mean square error, and mean absolute error, to find the best parameters for a spindle thermal displacement model. (3) The third method used system recognition to determine similarity to actual data by dividing the model into rise time and stable time. The rise time was controlled to explore the accuracy of prediction of the model at different intervals. The experimental results show that the actual measured temperatures were very close to those obtained in the Comsol analysis. The traditional model calculates prediction error values within single intervals, and so the model was divided to give rise time and stable time. The experimental results showed two error intervals, 19µm in the rise time and 15µm in the stable time, and these findings allowed the machining accuracy to be enhanced.

Keywords: linear regression; thermal displacement; spindle thermal elongation; finite element analysis; thermal error (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/4/949/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/4/949/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:4:p:949-:d:323042

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().