In this study, discrete wavelet decomposition is used to detect tool failure and to conduct the de-noising of the cutting force signal in a turning process. As a result of de-noising, the wavelet de-noising method is more effective than the FFT filtering technique that is typically used. An analysis of the approximation and the detail coefficients of the cutting force signal confirmed that the onset time of tool failure and chatter vibration was successfully detected.
机构:
Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R ChinaChinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R China
Lin, J
;
Qu, LS
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R ChinaChinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R China
机构:
Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R ChinaChinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R China
机构:
Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R ChinaChinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R China
Lin, J
;
Qu, LS
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R ChinaChinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R China
机构:
Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R ChinaChinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100080, Peoples R China