As a key parameter, stiffness determines the dynamic characteristics of the bearing and the spindle unit. However, the interaction of the spindle speed, initial preload, and cutting force will change the bearing stiffness characteristics during the running process cause the thermal expansion of spindle unit components. Aiming at real-time online monitoring of the thermal characteristics of machine tool spindle bearing stiffness, this paper proposed a fiber Bragg grating (FBG) sensors network. And under different axial loads, combined axial and specific radial load, the bearing temperature rise, thermally induced preload, and thermal stiffness are studied. The results show that the thermal stiffness of the bearing decreases with the increase of the spindle speed, and there is an optimal initial preload at the speed to maximize the thermal stiffness of the bearing, and the thermally induced preload has an additional pre-tightening effect on the bearing.