A reliability assessment method based on support vector machines for CNC equipment

被引:0
|
作者
WU Jun1
2 State Key Laboratory of Digital Manufacturing Equipment & Technology
3 Department of Mechanical Engineering
机构
关键词
reliability assessment; least squares support vector machines; performance degradation; radial basis function; parameter optimization;
D O I
暂无
中图分类号
TH17 [机械运行与维修];
学科分类号
0802 ;
摘要
With the applications of high technology,a catastrophic failure of CNC equipment rarely occurs at normal operation conditions.So it is difficult for traditional reliability assessment methods based on time-to-failure distributions to deduce the reliability level.This paper presents a novel reliability assessment methodology to estimate the reliability level of equipment with machining performance degradation data when only a few samples are available.The least squares support vector machines(LS-SVM) are introduced to analyze the performance degradation process on the equipment.A two-stage parameter optimization and searching method is proposed to improve the LS-SVM regression performance and a reliability assessment model based on the LS-SVM is built.A machining performance degradation experiment has been carried out on an OTM650 machine tool to validate the effectiveness of the proposed reliability assessment methodology.
引用
收藏
页码:1849 / 1857
页数:9
相关论文
共 50 条
  • [41] Hybrid diagnosis method based on evolutionary algorithm and support vector machines
    Ding, Wei
    Wei, Xun-Kai
    He, Li-Ming
    2007 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2007, : 1072 - 1076
  • [42] A Method of Plant Classification Based on Wavelet Transforms and Support Vector Machines
    Liu, Jiandu
    Zhang, Shanwen
    Deng, Shengli
    EMERGING INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS, PROCEEDINGS, 2009, 5754 : 253 - +
  • [43] Novel Method of Predicting Network Bandwidth Based on Support Vector Machines
    沈伟
    冯瑞
    邵惠鹤
    Journal of Beijing Institute of Technology(English Edition), 2004, (04) : 454 - 457
  • [44] Image watermarking method in multiwavelet domain based on support vector machines
    Peng, Hong
    Wang, Jun
    Wang, Weixing
    JOURNAL OF SYSTEMS AND SOFTWARE, 2010, 83 (08) : 1470 - 1477
  • [45] Soft-sensor modeling method based on support vector machines
    Zhang, MG
    Yan, WW
    ICEMI 2005: CONFERENCE PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL 7, 2005, : 208 - 213
  • [46] Research on Forecasting Method Based on Genetic Algorithms and Support Vector Machines
    Xiao, Chengyong
    Guo, Pengyan
    Feng, Zhipeng
    Deng, Yongsheng
    APPLIED MECHANICS AND MECHANICAL ENGINEERING, PTS 1-3, 2010, 29-32 : 2603 - +
  • [47] An incremental updating method for Support Vector Machines
    Liu, YG
    Chen, Q
    Tang, YC
    He, QM
    ADVANCED WEB TECHNOLOGIES AND APPLICATIONS, 2004, 3007 : 426 - 435
  • [48] A simple decomposition method for support vector machines
    Hsu, CW
    Lin, CJ
    MACHINE LEARNING, 2002, 46 (1-3) : 291 - 314
  • [49] On the convergence of the decomposition method for support vector machines
    Lin, CJ
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2001, 12 (06): : 1288 - 1298
  • [50] Balance method for imbalanced support vector machines
    Department of Applied Mathematics, Xidian University, Xi'an 710071, China
    不详
    不详
    Moshi Shibie yu Rengong Zhineng, 2008, 2 (136-141):