End Milling Tool Breakage Detection Using Dual-tree Complex Wavelet Transform
(0) Signal analysis techniques are of significant importance for effective detection of tool breakage in end milling especially in finishing milling.Wavelet transforms (WT) share significant values in analyzing the non-stationary contents like machinery wave signals.In this paper,a technique based on the dual-tree complex wavelet transform (DTCWT) is proposed for detection of tool breakage via acoustic emission (AE) signals generated in end milling process.DTCWT enjoys attractive properties such as better shift-invariance and reduced spectral aliasing in comparison with classical dyadic wavelet transform (DWT) and empirical mode decomposition (EMD).These advantages of the DTCWT arise from the relationship between the two dual-tree wavelet basis functions,which enhance the performance of extracting the fault signatures of periodic impact features embedded in the comprehensive vibration signals.The effectiveness of this method has been validated in practical application on a CNC vertical milling machine tool.The results show that the proposed method successfully identifies the incipient fault features of cutting tools in end milling process.
Dual-tree complex wavelet transform Acoustic emission Tool breakage detection End milling
Chunlin Zhang Hongrui Cao Zhengjia He Bing Li
State Key Laboratory for Manufacturing Systems Engineering,Xian Jiaotong University Xian 710049,China
国际会议
南京
英文
1-4
2013-08-20（万方平台首次上网日期，不代表论文的发表时间）