Chatter detection in robotic drilling operations combining multi-synchrosqueezing transform and energy entropy

  • Jianfeng Tao
  • Hongwei Zeng
  • Chengjin QinEmail author
  • Chengliang Liu


Robotic drilling shows higher efficiency and precision than the manual drilling, which has great application prospects in the aviation manufacturing. Nevertheless, due to the detrimental effects on surface quality, tool wear, the safety of the robot and machining efficiency, chatter vibration has been a major obstacle to achieve stable and efficient robotic drilling. Therefore, it is particularly significant to detect and manage to suppress the chatter as early as possible. This paper presents a novel approach to identify the chatter in robotic drilling process based on multi-synchrosqueezing transform (MSST) and energy entropy. To begin with, matrix notch filters are designed to effectively eliminate the interference of spindle rotating frequency and its harmonics to the measured vibration signal. Subsequently, the filtered signal is processed by the MSST to obtain concentrated time-frequency representation. Then, the signal is divided equally into finite frequency bands and the subcomponent corresponding to each frequency band is reconstructed through the reverse MSST. Finally, in consideration of the change of the vibration signal in frequency and energy distribution when chatter occurs, the energy entropy is computed as the chatter detection indicator. The proposed chatter detection method was validated by robotic drilling experiments with different tools, machining parameters, and workpiece material, and the results indicate that the proposed method can effectively detect the chatter before it is fully developed and recognize the chatter earlier than the synchroextracting-based method.


Robotic drilling process Chatter detection Matrix notch filter Multi-synchrosqueezing transform Energy entropy 


Funding information

This work was partially supported by the National Key Research and Development Program of China (Grant Nos. 2017YFB1302601 and 2018YFB1306703).


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Jianfeng Tao
    • 1
  • Hongwei Zeng
    • 1
  • Chengjin Qin
    • 1
    Email author
  • Chengliang Liu
    • 1
  1. 1.State Key Laboratory of Mechanical System and Vibration, School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghaiChina

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