Abstract
This paper is concerned with study for chatter prediction in high-speed end milling operations. Chatter vibration occurring in mechanical machining gives rise to poor surface finish and dimensional accuracy in machined part, reduction of tool life, and even damages machine tools. It is various kinds of researchers concerning its prediction and avoidance have been carried out over the last several decades. The purpose of this study is to develop an expert system for predicting chatter vibrations in high-speed end milling using wavelet transform and a fuzzy neural network model with pruning process. The proposed method is applied to a jig griding machine, and the results demonstrate the effectiveness of the chatter prediction procedure.
