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Chatter detection in milling process based on synchrosqueezing transform of sound signals

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Abstract

Chatter is a self-excited vibration between the workpiece and tool with negative effects. In this work, a chatter detection method is proposed based on synchrosqueezing transform (SST) of sound signals. Firstly, the SST is used to analyze the sound signals recorded with the microphone and a time-frequency representation is obtained. Then, filtering is conducted to remove the disturbance of tooth passing frequency and its harmonics in time-frequency domain. Next, singular value decomposition (SVD) method is employed to condense the TF matrix and the first-order singular value is calculated as the chatter indicator. Finally, chatter threshold is set based on 3σ criterion for the detection of chatter occurrence. The proposed method is validated with cutting tests, and the results show that the method has great potential to be used for the online chatter detection of high-speed milling process.

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Authors and Affiliations

  1. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, Xi’an Jiaotong University, Xi’an, 710049, China

    Hongrui Cao & Yiting Yue

  2. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Xuefeng Chen & Xingwu Zhang

Authors
  1. Hongrui Cao
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  2. Yiting Yue
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  3. Xuefeng Chen
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  4. Xingwu Zhang
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Correspondence to Hongrui Cao.

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Cao, H., Yue, Y., Chen, X. et al. Chatter detection in milling process based on synchrosqueezing transform of sound signals. Int J Adv Manuf Technol 89, 2747–2755 (2017). https://doi.org/10.1007/s00170-016-9660-7

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  • DOI: https://doi.org/10.1007/s00170-016-9660-7

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