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.
Highlights
IntroductionHigh precision and accuracy in processing have become a very important requirement
Modern machine tools, those that process metal, have become very smart.High precision and accuracy in processing have become a very important requirement
The results showed that multiple linear regression and nonlinear exponential regression can limit the thermal error to within 5%
Summary
High precision and accuracy in processing have become a very important requirement. Such machines used in production get hot, and thermal expansion is the main cause of errors in accuracy [1,2]. The heat that causes thermal deformation of the main shaft, accounts for 40% to 70% [4] or 30% to 50% [5] of the thermal deformation in machine tools. Other approaches have been made which include: cooling the spindle to reduce expansion; maintaining the temperature of the spindle within a particular range to keep dimensional changes to a minimum; and conduction of the heat from a high temperature zone
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