Research on thermal displacement modeling of the variable pressure preload motorized spindle

There is the problem of machining quality caused by the thermal displacement of the motorized spindle at variable speed. To address this issue, an experimental method of natural speed reduction for the motorized spindle under different preload forces is proposed by building an experimental platform of the variable pressure preload motorized spindle. The frictional heat generation model of bearings based on the energy conservation theory is formulated, and the function relationship between preload forces and bearing heat generation are constructed. On this basis, the influence law of bearings temperature leading to the thermal displacement of the spindle is further investigated. The temperature data of bearings and the time of the motorized spindle with preload forces of 1 450, 1 550 and 1 700 N are used as input to construct a BP neural network thermal displacement prediction model of the motorized spindle. Results show that the fomulated thermal displacement prediction model can effectively predict the thermal displacement of the motorized spindle, and the residuals of the prediction model are within 0.5 μm. The research results provide a new method for the intelligent compensation of thermal error in high-precision machine tool spindles. © 2022, Science Press. All right reserved.