, Volume 26, Issue 1, pp 158-165

Temperature variable optimization for precision machine tool thermal error compensation on optimal threshold

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Abstract

Machine tool thermal error is an important reason for poor machining accuracy. Thermal error compensation is a primary technology in accuracy control. To build thermal error model, temperature variables are needed to be divided into several groups on an appropriate threshold. Currently, group threshold value is mainly determined by researchers experience. Few studies focus on group threshold in temperature variable grouping. Since the threshold is important in error compensation, this paper arms to find out an optimal threshold to realize temperature variable optimization in thermal error modeling. Firstly, correlation coefficient is used to express membership grade of temperature variables, and the theory of fuzzy transitive closure is applied to obtain relational matrix of temperature variables. Concepts as compact degree and separable degree are introduced. Then evaluation model of temperature variable clustering is built. The optimal threshold and the best temperature variable clustering can be obtained by setting the maximum value of evaluation model as the objective. Finally, correlation coefficients between temperature variables and thermal error are calculated in order to find out optimum temperature variables for thermal error modeling. An experiment is conducted on a precise horizontal machining center. In experiment, three displacement sensors are used to measure spindle thermal error and twenty-nine temperature sensors are utilized to detect the machining center temperature. Experimental result shows that the new method of temperature variable optimization on optimal threshold successfully worked out a best threshold value interval and chose seven temperature variables from twenty-nine temperature measuring points. The model residual of z direction is within 3 μm. Obviously, the proposed new variable optimization method has simple computing process and good modeling accuracy, which is quite fit for thermal error compensation.

This project is supported by Jiangsu Provincial Prospective Joint Research Foundation for Industry-University-Research of China (Grant No. BY2009102), and Henan Provincial Major Scientific and Technological Projects of China (Grant No. 102102210050)
ZHANG Ting, born in 1979, is currently a PhD candidate at College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, China. She is a lecturer at Nanjing Institute of Technology, China. Her research interests include machine tool accuracy control and error compensation.
YE Wenhua, born in 1965, is currently a professor at Nanjing University of Aeronautics and Astronautics, China. His research interests include computer integrated manufacturing, machine tool accuracy control.
LIANG Ruijun, born in 1974, is currently an associate professor at Nanjing University of Aeronautics and Astronautics, China. Her research interests include dynamic modeling of mechanical system and machine tool thermal error compensation.
LOU Peihuang, born in 1962, is currently a professor at Nanjing University of Aeronautics and Astronautics, China. His research interests include computer integrated manufacturing and digital manufacturing.
YANG Xiaolan, born in 1964, is currently a professor at Nanjing Institute of Technology, China. Her research interests include mechanical dynamics, vibration shock theory and control.