Grinding monitoring system based on power and acoustic emission sensors

Improvement of monitoring techniques is essential to make the complex grinding and dressing process more reliable, economical and user friendly. A system utilizing data fusion from different sensor sources and Al methods combined with a graphical user interface has been applied for this purpose. The main task of the grinding monitoring system is the detection of disturbances and the grinding cycle optimization based on the AE and power signal. The influence of different dressing parameters on the AE-signal has been investigated and a dressing monitoring system is proposed. Reliable data acquisition techniques, which make a continuous scanning of such wide bandwidth signals possible, have been applied.