Prediction of case depth for deep carburising heat treatments based on the spatial gradient feature of the grain size profile

Abstract

ABSTRACT Precise evaluation of carburising heat treatment is necessary to avoid failure and degradation of high-performance industrial mechanical components. In this work, a novel non-destructive detection method is proposed for the deep carburised case depth (>2 mm) combining spatial ultrasonic backscatter technique and linear regression model. To create various carburised case depths, three groups of cylindrical 20CrMnMo steel samples were heat-treated in various cycles (Carburising, diffusing, quenching at 850–870°C (holding in range of 2.5–3 h) and tempering). The carburising heat treatment results in a gradient microstructure within the surface region caused by changes in grain size. We employed a transverse-to-transverse scattering model to provide the gradient feature of the grain size profile in the depth direction. The extracted gradient profiles of different carburised case depths exhibit two overlapped growth rates with high- and low-slope factors, respectively. With the increase of the carburised case depth, the positions of the centre points increase and the slope factors decrease. Based on these observations, a modified double sigmoidal function was utilised to parametrise the gradient profile curve. The relationship among the selected gradient feature parameters and various carburised case depths has been established. The predicted results were compared to hardness measurements with good agreement.