Abstract
In grinding operations, one of the most important problems is to determine the tool life of a grinding wheel accurately. Frequent dressing wastes not only time but also the abrasive materials, which becomes crucial when an expensive tool such as a CBN wheel is used. Grinding with a worn wheel causes the workpiece surface roughness to increase and often results in the occurrence of such troubles as chatter vibration. However, highly reliable techniques to monitor the tool life of a grinding wheel have not been established yet, and the wheel life is, in most cases, determined by human operators based on their observations and expertise. In this study, the monitoring method using an acoustic emission (AE) sensor is proposed to define the wheel tool life in the cylindrical grinding process. The contact detection between the wheel and the dresser, as well as the evaluation of the grain sharpness, are attained by monitoring the amplitude level of the AE signal. The chatter vibration is, on the other hand, detected by observing the power spectrum of the rectified AE signal, and well recognized by means of the neural network.
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