Optimization of Measuring Points for High-speed Motorized Spindle Thermal Error

摘要

According to the location and number of temperature measuring points of the motorized spindle thermal error, a new method for optimizing the locations of thermal key points is proposed. Firstly, temperature measuring points are divided into groups by using fuzzy clustering method. Secondly, grey correlation model is adopted to analyze emphasis of each measuring point to thermal deformation in temperature field distribution of motorized spindle. Finally, temperature measuring points have been optimally selected based on modified coefficient of determination. Comparing to the conclusion of the existed literature, the results show that this method is feasibility and validity. The method can reduce the temperature variables and modeling time, and supply the theoretic support for the engineering experience.