Metallographic method for temperature measurement: Reconstruction of grinding temperature field based on critical austenitizing depth and cyclic feedback algorithm

Abstract

Effectively measuring and predicting the grinding temperature is significant for accurately controlling machined surface quality. However, the spatial limitations of the contact area and the time-varying of heat sources make the accurate acquisition of grinding temperature challenging. Existing methods have made critical achievements, but further exploration is still desired. To this end, a metallographic method for temperature measurement is proposed, which uses the thermal reference reflected by metallographic images combined with a cyclic feedback algorithm to reconstruct the grinding temperature field. Specifically, dry grinding thermal-force synchronous measurement experiments are carried out for carbon steel, and the mapping relationship between the grinding heat transient characteristics and metallurgical transformations diversity in the surface material is established. The improved image recognition algorithm is applied with metallographic detection to achieve accurate localization of the critical austenitizing depth. Afterwards, a cyclic feedback algorithm based on differential heat transfer is proposed to solve the dynamic distribution of the grinding temperature field (error within 10%) under random heat sources. The results show that the parabolic heat source can better describe the distribution of heat flow density in the contact area under dry grinding, and the heat flow into the workpiece is about 30% of the total energy. This study fills the blank of the metallographic method for solving grinding temperature, which helps profoundly understand the interaction mechanism between processing heat and metallurgical transformation and promotes the development of advanced temperature measurement and prediction technology.