• DocumentCode
    2339830
  • Title

    Reliability Assessment of Machine Tool Spindle Bearing Based on Vibration Feature

  • Author

    Dayong, Jiang ; Taiyong, Wang ; Yongxiang, Jiang ; Lu, Liu ; Miao, Hu

  • Author_Institution
    Sch. of Mech. Eng., TianJin Univ., Tianjin, China
  • Volume
    2
  • fYear
    2010
  • fDate
    18-20 Dec. 2010
  • Firstpage
    154
  • Lastpage
    157
  • Abstract
    Traditional reliability analysis of CNC Machine Tools based on mathematical statistics method, which have to obtain a large number of failure datas through accelerated life test, It is not suitable for high-precision products. In this case, machining features based on the current machine performance degradation datas can provide more useful information about the reliability analysis. Based on using failure datas to model and the current equipment vibration signal feature extraction, a new method of reliability analysis by using proportional hazard models is proposed in this paper. By this method, not only the low-level information(such as the vibration feature of equipment) and high-level information(like the reliability of the equipment) of CNC machine tools can be linked but also the reliability model can be established based on the extraction of vibration characteristics of spindle bearing.
  • Keywords
    Weibull distribution; condition monitoring; machine tool spindles; reliability; vibrations; CNC machine tools; computerised numerical control; machine tool spindle bearing; machining features; mathematical statistics method; proportional hazard models; reliability analysis; reliability assessment; vibration feature; vibration signal feature extraction; Proportional hazards model; Spindle bearings; Weibull distribution; reliability modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Manufacturing and Automation (ICDMA), 2010 International Conference on
  • Conference_Location
    ChangSha
  • Print_ISBN
    978-0-7695-4286-7
  • Type

    conf

  • DOI
    10.1109/ICDMA.2010.105
  • Filename
    5701372