Estimation of Dynamic Grinding Wheel Wear in Plunge Grinding

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. © 2017 The Authors

Robust realtime instrument tracking in ultrasound images for visual servoing

Abstract-Minimally invasive surgery in combination with ultrasound (US) imaging imposes high demands on the surgeon's hand-eye-coordination capabilities. A possible solution to reduce these requirements is minimally invasive robotic surgery in which the instrument is guided by visual servoing towards the goal defined by the surgeon in the US image. This approach requires robust tracking of the instrument in the US image sequences which is known to be difficult due to poor image quality. This paper presents computer vision algorithms and results of visual servoing experiments. Adaptive thresholding according to Otsu's method allows to cope with large intensity variations of the instrument echo. Subsequently applied morphological operations suppress noise and echo artefacts. A fast labelling algorithm based on run length coding allows for realtime labelling of the regions. A heuristic exploiting region size and region velocity helps to overcome ambiguities. The overall computation time is less than 10 ms per frame on a standard PC. The tracking algorithm requires no information about texture and shape which are known to be very unreliable in US image sequences. Experimental results for different instrument materials (polyvinyl chloride, polyurethane, nylon, and plexiglas) are given, illustrating the performance of the proposed approach: when chosing the appropriate material the reconstructed trajectories are smooth and only few outliers occur. As a consequence, the visual servoing loop showed to be robust and stable