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Caixu YUE, Zhenlong XIE, Xianli LIU, Mingwei ZHAO. Chatter prediction of milling process for titanium alloy thin-walled workpiece based on EMD-SVM[J]. Journal of Advanced Manufacturing Science and Technology , 2022, 2(2): 2022010. DOI: 10.51393/j.jamst.2022010
Citation: Caixu YUE, Zhenlong XIE, Xianli LIU, Mingwei ZHAO. Chatter prediction of milling process for titanium alloy thin-walled workpiece based on EMD-SVM[J]. Journal of Advanced Manufacturing Science and Technology , 2022, 2(2): 2022010. DOI: 10.51393/j.jamst.2022010
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Chatter prediction of milling process for titanium alloy thin-walled workpiece based on EMD-SVM

  • Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China

Funds: 

This study was co-supported by the Projects of Outstanding Youth Fund of Heilongjiang Province (No. YQ2019E029) and International Cooperation and Exchanges NSFC (No. 51720105009).

  • Received Date: January 19, 2022
  • Revised Date: February 11, 2022
  • Accepted Date: March 17, 2022
  • Available Online: March 29, 2022
    Graphical Abstract
    • Abstract
  • Easy cutting vibration of Titanium alloy thin-walled structural components in processing process directly influences the quality of part machining surface. So, the chatter prediction has become a research hotspot. The milling process of Ti-6Al-4V framework parts for hard alloy cutter is researched and chatter prediction methods are proposed to solve the chatter problem generated in milling process. The signals in milling process are comprehensively considered to work out the stability boundary and the chatter prediction model based on Empirical Mode Decomposition (EMD) and Support Vector Machine (SVM). The stability lobe diagram is utilized to select experiment parameter for experiment, in which the 1/3-2/3 position of framework parts chatters easily in processing. The model training in experiment aims to monitor the time of chatter, with the recognition precision of 97.50%.
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    • References (25)
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