Estimation of Dynamic Grinding Wheel Wear in Plunge Grinding

Abstract

Using conventional grinding wheels, self-excited vibrations are one of the most limiting factors in terms of productivity and process stability in cylindrical plunge grinding. Depending on the dynamic behavior of the workpiece and machine, vibrations of the workpiece copy on the grinding wheel's surface, caused by uneven wear. This results in increasing waviness of the grinding wheel and by that, increasing workpiece vibration. Electromagnetic actuators are capable of influencing the dynamic process forces and therefore, the wear. The authors pursue the objective, to achieve an active control of the tool wear for low workpiece vibration and high workpiece quality. Therefore, a tool-wear-model which enables the estimation of the grinding wheel's surface is proposed. The parameterization of the model is realized carrying out a set of reference processes with subsequent identification. Aside from the dynamic tool wear, the workpiece oscillation is simulated by the model. A Kalman Filter is utilized to adjust the model onto the current process using the measured workpiece oscillation. Thus, it is possible to achieve an online estimation of the wave amplitude and phase angle on the grinding wheel's surface as well as their progression.