An Empirical Model for Prediction of Residual Stress Based on Grinding Forces

Abstract

Residual stress has a significant influence on mechanical strength of a manufactured part and is considered to be related with process parameters and grinding signals. This paper investigates the relationship between residual stress and forces in the grinding of maraging steel 3J33. Features in time and frequency domains are extracted from tangential and normal grinding forces via various signal processing techniques. A two-round selection based on the statistical criterion is proposed to choose the best features that are related to the residual stress in the surface layer. The selected features are combined linearly in order to develop an empirical regression model that is capable of predicting residual stress well. The predicted residual stress values are compared with those measured from the experiment performed under different process parameters, and the result shows a favorable agreement quantitatively.