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Analysis of Q-factor’s identification ability for thin-walled part flank and mirror milling chatter

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Abstract

Due to its relatively high gravity material removal, the thin-walled part machining would go through a complex process, from stable to unstable and/or reverse repeatedly. As a result, the monitored signals generally exhibit full-oscillatory behaviors, which require that the chatter indicators should meet the dynamic conditions. However, the conventional indicators, including time domain indicators and time-frequency domain indicators, could only capture the state mutation point in the continuous process. In this paper, a novel chatter indicator, Q-factors, is proposed for chatter detection. The relationship between Q-factor and signal oscillatory behavior is illustrated from the perspective of signal’s frequency characteristics and tool-workpiece system’s response. Chatter indicator’s identification ability for thin-walled part flank and mirror milling is analyzed, i.e., its ability to express characteristics of machining state, sensibility to change machining state, and its chatter-related information inclusion. It can be indicated that as a multi-dimensional indicator, Q-factor can be used to identify chatter-related signal component and quantify the level of chatter simultaneously. The value of Q-factor exhibits obvious difference between stable state and chatter state. The obvious mutation at the place where the machining state changes will supply more useful and effective information for the following chatter prediction and suppression before the chatter is completely developed.

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Funding

This work is supported by National Basic Research Program Funding Agency of China (Grant No. 2014CB046604), by the Fundamental Research Funds for the Central Universities (Grant No. DUT17JC16), and by Open Research Fund of Key Laboratory of High Performance Complex Manufacturing, Central South University (Grant No. Kfkt2016-05).

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Authors and Affiliations

  1. Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, 116024, China

    Haibo Liu, Qile Bo, Hao Zhang & Yongqing Wang

  2. School of Mechanical Engineering, Dalian University of Technology, Linggong Road No. 2, Ganjingzi District, Dalian City, Liaoning Province, China

    Qile Bo

Authors
  1. Haibo Liu
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  2. Qile Bo
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  3. Hao Zhang
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  4. Yongqing Wang
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Correspondence to Qile Bo.

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Liu, H., Bo, Q., Zhang, H. et al. Analysis of Q-factor’s identification ability for thin-walled part flank and mirror milling chatter. Int J Adv Manuf Technol 99, 1673–1686 (2018). https://doi.org/10.1007/s00170-018-2580-y

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  • DOI: https://doi.org/10.1007/s00170-018-2580-y

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