A functional approach to integrating grinding temperature modeling and Barkhausen noise analysis for prediction of surface integrity in bearing steels

The use of NDE techniques such as Barkhausen Noise Analysis (BNA) for detection of grinding induced thermal damage is often application specific due to variables in the grinding process. In this paper, Malkin's grinding energy partition model is applied in conjunction with BNA to reliably predict occurrence of thermal damage in through-hardened bearing steels independent of grinding variables. Various intensities of material transformation such as surface, sub-surface retempering and rehardening were accurately detected and validated by metallography and residual stress analysis. The results demonstrate that material-specific models independent of grinding process variables can be effectively utilized to predict thermal damage.