The Fractal Characteristic of Vibration Signals in Different Milling Tool Wear Periods

There are a wide variety of condition monitoring techniques currently used for the recognition and diagnosis of machinery faults. Tool wear often results in chaotics on milling process. Little research has been carried out about the occurrence and detection of chaotic behavior in time series signal of tool vibration. In the paper the vibration acceleration signal based on the operating stages of tool wear is established for the analysis of the correlation dimension of the operating stages of tool wear. Correlation dimension is calculated to recognize the tool wear operating conditions. Finally some experimental results from the fractal characteristic show that there are distinct differences in the correlation dimension in different tool wear conditions and close the correlation dimension in same tool wear conditions. The correlation dimension not only can be used as important scientific basis for monitoring tool wear, but also complement of other characteristic picking up method.