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  • 标题:Tool Breakage Detection of Milling Cutter Insert Based on SVM
  • 本地全文:下载
  • 作者:Shixu Sun ; Xiaofeng Hu ; Weili Cai
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2019
  • 卷号:52
  • 期号:13
  • 页码:1549-1554
  • DOI:10.1016/j.ifacol.2019.11.420
  • 语种:English
  • 出版社:Elsevier
  • 摘要:The paper deals with a new method for the tool breakage monitoring of milling cutter insert through acoustic emission (AE) technique. An insert breakage detection method based on support vector machine (SVM) is proposed, which consists of off-line phase and on-line phase. In the off-line phase, 13 AE signal features were extracted as input and then the SVM model was established and optimized. In the on-line phase, the constructed model was used to detect insert breakage. The proposed method was applied and validated by an experiment conducted on a rotor slot milling machine in a factory. The result shows the validity and practicability of this method.
  • 关键词:Keywordstool breakage monitoringbreakage detectionacoustic emissionsupport vector machinerecursive feature elimination
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