Prediction of tool breakage in face milling using support vector machine

被引：0
|
作者：
Hsueh, Yao-Wen [1 ]
Yang, Chan-Yun [1 ]
机构：
[1] Department of Mechanical Engineering, Technology and Science, Institute of Northern Taiwan, No. 2, Xueyuan Rd., Peitou, 112, Taipei, Taiwan
来源：
International Journal of Advanced Manufacturing Technology | 2008年 / 37卷 / 9-10期
关键词：
A new approach is proposed using a support vector machine (SVM) to classify the feature of the cutting force signal for the prediction of tool breakage in face milling. The cutting force signal is compressed by averaging the cutting force signals per tooth to extract the feature of the cutting force signal due to tool breakage. With the SVM learning process; the output of SVM's decision function can be utilized to identify a milling cutter with or without tool breakage. Experimental results are presented to verify the feasibility of this tool breakage prediction system in milling operations. © 2007 Springer-Verlag London Limited;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Journal article (JA)
引用
收藏
页码：872 / 880
相关论文
共 50 条
  • [1] Prediction of tool breakage in face milling using support vector machine
    Yao-Wen Hsueh
    Chan-Yun Yang
    The International Journal of Advanced Manufacturing Technology, 2008, 37 (9-10) : 872 - 880
  • [2] Prediction of tool breakage in face milling using support vector machine
    Hsueh, Yao-Wen
    Yang, Chan-Yun
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2008, 37 (9-10): : 872 - 880
  • [3] Tool breakage diagnosis in face milling by support vector machine
    Hsueh, Yao-Wen
    Yang, Chan-Yun
    JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2009, 209 (01) : 145 - 152
  • [4] Sensing Tool Breakage in Face Milling By Support Vector Machine
    Hsueh, Yao-Wen
    Yang, Chan-Yun
    ADVANCES IN MATERIALS AND PROCESSING TECHNOLOGIES II, PTS 1 AND 2, 2011, 264-265 : 991 - 996
  • [5] Tool breakage detection using support vector machine learning in a milling process
    Cho, S
    Asfour, S
    Onar, A
    Kaundinya, N
    INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2005, 45 (03): : 241 - 249
  • [6] Prediction of Machine Tool Condition Using Support Vector Machine
    Wang, Peigong
    Meng, Qingfeng
    Zhao, Jian
    Li, Junjie
    Wang, Xiufeng
    9TH INTERNATIONAL CONFERENCE ON DAMAGE ASSESSMENT OF STRUCTURES (DAMAS 2011), 2011, 305
  • [7] Support vector regression based tool wear assessment in face milling
    Bhattacharyya, P.
    Sanadhya, S. K.
    2006 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-6, 2006, : 1562 - +
  • [8] Milling Chatter Prediction Based on the Information Entropy and Support Vector Machine
    Chen Bing
    Yang Jie
    Zhao Ju
    Ren Jingbo
    PROCEEDINGS OF THE 2015 INTERNATIONAL INDUSTRIAL INFORMATICS AND COMPUTER ENGINEERING CONFERENCE, 2015, : 376 - 380
  • [9] SENSING TOOL BREAKAGE IN FACE MILLING WITH A NEURAL-NETWORK
    TARNG, YS
    HSEIH, YW
    HWANG, ST
    INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 1994, 34 (03): : 341 - 350
  • [10] CNC internal data based incremental cost-sensitive support vector machine method for tool breakage monitoring in end milling
    Xu, Guangda
    Zhou, Huicheng
    Chen, Jihong
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 74 : 90 - 103
12345