2017
DOI: 10.1016/j.measurement.2017.02.035
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Tool condition monitoring technique for deep-hole drilling of large components based on chatter identification in time–frequency domain

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Cited by 62 publications
(18 citation statements)
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“…For the purpose of NC machining of turbo drill impeller, Wang et al put forward a comprehensive processing method based on UG software [4].…”
Section: Literature Reviewmentioning
confidence: 99%
“…For the purpose of NC machining of turbo drill impeller, Wang et al put forward a comprehensive processing method based on UG software [4].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Zhang et al [10] used multiple sensor data, such as cutting vibration data and power data, as well as actual processing parameters to develop a system to realize tool condition-monitoring and life estimation efficiently, which is widely used in small and medium-sized enterprises. Uekita et al [11] presented a tool condition monitoring technique combining short-time Fourier transform and spectral kurtosis analysis to identify chatter process, which will guarantee the machining precision of large-size components and provide tool state information. Javier et al [12] proposed a Gaussian mixture model based on dynamic probabilistic clustering for tool condition monitoring.…”
Section: Introductionmentioning
confidence: 99%
“…There are other methods devoted to the applications of online chatter detection, such as chatter identification based on wavelet transform (WT) and support vector machine (SVM), (11) Hilber-Huang transform (HHT), (12) and short-time Fourier transform (STFT). (13,14) The time-frequency signal processing tools, such as STFT, WT, HHT, and Teager-Huang transform (THT), are gradually applied to dynamic signal analyses owing to their superior performance in both time and frequency domains simultaneously. The signal-resolving powers of STFT and WT are limited by the time window function and the mother wavelet type, respectively.…”
Section: Introductionmentioning
confidence: 99%