A Statistical Model of Equivalent Grinding Heat Source Based on Random Distributed Grains

Abstract

Accurate information about the evolution of the temperature field is a theoretical prerequisite for investigating grinding burn and optimizing the process parameters of grinding process. This paper proposed a new statistical model of equivalent grinding heat source with consideration of the random distribution of grains. Based on the definition of the Riemann integral, the summation limit of the discrete point heat sources was transformed into the integral of a continuous function. A finite element method (FEM) simulation was conducted to predict the grinding temperature field with the embedded net heat flux equation. The grinding temperature was measured with a specially designed in situ infrared system and was formulated by time–space processing. The reliability and correctness of the statistical heat source model were validated by both experimental temperature–time curves and the maximum grinding temperature, with a relative error of less than 20%. Finally, through the FEM-based inversed calculation, an empirical equation was proposed to describe the heat transfer coefficient (HTC) changes in the grinding contact zone for both conventional grinding and creep feed grinding.