In contrast to the well-established stability prediction tools, a robust real-time stability indicator is proposed for micromilling process, and it opens the possibility of online chatter avoidance based on successful detection. In this paper, a robust and easy-to-compute stability indicator is presented. This approach exploits the virtue of a stable milling process—the displacement of the vibrating tool repeats with a period of tooth passing. It has been observed that the standard deviation of the tool displacement sampled at once per tooth passing frequency is indicative of chatter, where a low standard deviation coincides with stable cutting. An increase in standard deviation is the direct consequence of an increase in asynchronous motion of the tool, coinciding with chatter. As it is also well known, this asynchronous vibration of the tool results in distinct marks on the workpiece surface. This paper presents the experimental validation of this real-time stability indicator. The ease of implementation makes the presented stability indicator a strong candidate for applications in chatter avoidance based on detection. The results are also verified against the standard stability prediction method.
Experimental validation of the suitability of virtualization-based replication for fault tolerance in real-time control of electric grids
