Study of the temperature distribution of a machine tool spindle bearing based on FBG quasi-distributed sensing

Abstract

Temperature field distribution of a machine tool spindle system, especially the spindle bearing, directly determines the size and direction of the thermal errors, which will result in poor processing precision and degradation of mechanical property of the machine tool. Measurement and monitoring of spindle bearing temperature field are of great significance to enhance the manufacture precision of NC machine tool effectively. Traditional measurement methods of spindle bearing temperature field are single-point or two-point measurement and cannot be stuck to the bearing outer ring directly, thus the data being inaccurate. In this paper, a multipoint quasi-distributed sensing method based on embedded fiber Bragg grating (FBG) sensors was proposed to measure the temperature field of the outer ring of the bearing under three different working conditions: idling, uploading axial, and radial cutting force respectively. A traditional thermocouple had been used for measurement comparison and a finite element method (FEM) prediction method utilizing ANSYS Workbench software package had been presented for temperature distribution prediction. Experiment results showed that the measurement error between FBG and thermocouple was within 10%. The temperature distribution achieved by FBG sensors had great consistence with the simulation prediction model. It was demonstrated that this quasi-distributed sensing method can be applied to the measurement of spindle bearing temperature field distribution very well. Moreover, it can be seen as a significant means to effectively verify the thermal model of the spindle bearing integrated system.