Research on thermal stiffness of machine tool spindle bearing under different initial preload and speed based on FBG sensors

As a key parameter, stiffness determines the dynamic characteristics of both the bearing and the spindle unit. However, interactions between the spindle speed, initial preload, and cutting force caused by the thermal expansion of spindle unit components alter the bearing stiffness characteristics during the running process. Aiming to carry out real-time online monitoring of the thermal characteristics and their effect on the machine tool spindle bearing stiffness, a fiber Bragg grating (FBG) sensors network was proposed. Further, the effects were considered under various axial loads, combined axial, and specific radial load to study bearing temperature increase, thermally induced preload, and thermal stiffness. The results have shown that the bearing thermal stiffness of the bearing decreases with the increase of the spindle speed. Moreover, an optimal initial preload can be selected with respect to the speed to maximize the thermal stiffness. Finally, the thermally induced preload additionally pre-tightened the bearing.