M. Liang and D. Xu (Canada)
Chatter suppression, end milling, fuzzy approach.
This paper presents a fuzzy self-learning system for chatter suppression in milling processes. In this study, coherence function values of the two perpendicular vibration signals, combined with the mean vibration energy, were applied for chatter detection. The change and error of the coherence ratio and the error of mean vibration energy were used as the input to the fuzzy controller. The self-learning algorithm was applied to update the fuzzy rule base in response to on-line conditions. The experiments demonstrated that a more stable chatter suppression process can be achieved using the self-learning approach.
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