Abstract
The grindability of titanium alloys that are classified as hard-to-machine materials is studied in high-speed cylindrical grinding using a cubic boron nitride (CBN) wheel. The investigation is concerned with residual surface stresses, including the construction of its empirical model, orthogonal experiments with a CBN grinding wheel at a speed of 45–150 m/s, and prediction with the back propagation (BP) network. The results of residual surface stress measurements obtained in grinding experiments and simulation analysis for five sets of grinding conditions are compared, it can be seen that the empirical model is partially applicable to a Ti-6Al-4V titanium alloy (TC4) under examined grinding conditions. Generally, the calculation results with the empirical model exhibit a significant deviation from the data of actual measurements in some cases. The BP network possesses the function of complex nonlinear mapping and adaptive learning. So the BP network is adopted to predict the relation between residual surface stresses and three key grinding conditions accurately enough. The accuracy of the network is verified, which lays the foundation for its in practical application.
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